2026-04-04T03:07:44Z https://jurnal.upnyk.ac.id/index.php/telematika/oai

oai:jurnal.upnyk.ac.id:article/3195 2022-07-15T01:51:46Z telematika:GEN driver

Development of Applications for Simplification of Boolean Functions using Quine-McCluskey Method Nugroho, Eko Dwi Boolean Algebra Patrick POS Quine-McCluskey Method SOP Purpose: This research makes an application to simplify the Boolean function using Quine-McCluskey, because length of the Boolean function complicates the digital circuit, so that it can be simplified by finding other functions that are equivalent and more efficient, making digital circuits easier, and less cost.Design/methodology/approach: The canonical form is Sum-of-Product/Product-of-Sum and is in the form of a file, while the output is in the form of a raw and in the form of a file. Applications can receive the same minterm/maksterm input and do not have to be sequential. The method has been applied by Idempoten, Petrick, Selection Sort, and classification, so that simplification is maximized.Findings/result: As a result, the application can simplify more optimally than previous studies, can receive the same minterm/maksterm input, Product-of-Sum canonical form, and has been verified by simplifying and calculating manually.Originality/value/state of the art: Research that applies the petrick method to applications combined with being able to receive the same minterm/maksterm input has never been done before. The calculation is only up to the intermediate stage of the Quine-McCluskey method or has not been able to receive the same minterm/maksterm input. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3195 10.31315/telematika.v18i1.3195 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 27-36 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 27-36 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3195/3343 10.31315/telematika.v18i1.3195.g3343 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3376 2021-01-18T06:17:49Z telematika:AI driver

AKURASI DALAM ANALISA EKSPRESI EMOSI MANUSIA DENGAN MENGGUNAKAN TEKNOLOGI AUGMENTED REALITI DENGAN METODE NEURAL NETWORK DAN EIGENFACE Putra, Fajri Mulya Kodong, Frans Richard Florestiyanto, Mangaras Yanu Analisis Emosi Augmented Reality Kecerdasan Buatan Perusahan perusahaan di Indonesia cukup meningkat, dan banyak nya Lulusan muda dari perguruan tinggi di Indonesia sangat banyak belakangan ini. Maka Perusahaan butuh tenaga kerja yang cukup banyak dibutuhkan untuk meningkatkan kualitas Perusahaan tersebut.. Baik itu tenaga kerja dibidang IT ataupun dibagian Accounting dan tenaga teknisi ataupun pegawai umum untuk menjalankan Perusahaan tersebut. Karakteristik manusia itu memiliki banyak macam untuk menunjukan emosi nya. Dengan adanya sistem yang dapat diakses oleh Pihak HRD dengan perangkat mobile nya diharapakan dapat membantu untuk mendapatkan informasi lebih terhadap Calon Pegawai yang akan di wawancara oleh Pihak HRD. Analisis emosi merupakan kesimpulan dari effort emosi dalam mengungkapkan sesuatu dalam bentuk ekspresi. Pada peng ekspresian emosi untuk manusia biasanya memiliki cara yang berbeda beda. Dalam test wawancara untuk pencalonan pegawai baru dalam sebuah perusahaan memiliki banyak penilaian seperti penilian sikap, kontak mata , cara berbicara , bahasa tubuh dan ekspresi emosi. Dengan tenologi emotional face analysis dan voice emotion analysis dengan menggunakan teknologi Augmented Reality dan Artificial Intelligence yang nantinya digunakan sebagai tools untuk membantu pihak HRD dalam proses wawancara untuk mengumpulkan informasi tambahan terkait emosional psychology dari calon pegawai. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3376 10.31315/telematika.v1i1.3376 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 87-98 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 87-98 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3376/2561 10.31315/telematika.v1i1.3376.g2561 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3377 2021-01-18T06:17:49Z telematika:AI driver

TEXT MINING UNTUK MENDETEKSI PLAGIASI DOKUMEN DENGAN PENERAPAN STEMMING NAZIEF-ADRIANI DAN ALGORITMA SMITH-WATERMAN Meitaningsih, Alvika Aribowo, Agus Sasmito Cahyana, Nur Heri Plagiarisme Dokumen Smith Waterman Stemming Plagiarisme adalah tindakan menjiplak karya orang lain dan mengakui sebagai hasil karya pribadinya. Saat ini sudah banyak algoritma yang membahas cara mendeteksi plagiarisme dokumen teks seperti Cosine, Smith Waterman. Hasil penelitian sebelumnya menyatakan bahwa algoritma Smith Waterman memiliki keakurasian yang rendah, sehingga pada penelitian ini dilakukan pengembangan dari Algoritma Smith Waterman. Algortima Smith Waterman biasa digunakan didalam bidang bioinformatika untuk menentukan kesamaan DNA, akan tetapi dalam penelitian ini Algoritma Smith Waterman dapat diimplementasikan untuk mendeteksi dokumen. Proses pendeteksian kemiripan dokumen pertama-tama dilakukan proses preprocessing untuk menghilangkan imbuhan guna memudahkan proses pendeteksian dokumen yaitu dengan menggunakan stemming. Stemming yang digunakan dalam penelitian ini adalah Stemming Nazief & Adriani dan untuk mengukur tingkat keakurasian pada proses pendeteksian dokumen dilakukan perhitungan menggunakan algoritma Smith Waterman untuk mendapatkan hasil persentase kemiripan antar dokumen. Dari uji coba yang dilakukan penambahan preprocessing yaitu stemming mempengaruhi waktu proses pengujian karena pada proses preprocessing ini kata yang berimbuhan akan dikembalikan ke kata dasar dan dicocokan dengan data kamus yang ada didalam database. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3377 10.31315/telematika.v1i1.3377 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 99-110 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 99-110 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3377/2562 10.31315/telematika.v1i1.3377.g2562 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3378 2021-01-18T06:17:50Z telematika:AI driver

ALGORITMA COCKE YOUNGER KASAMI UNTUK DETEKSI STRUKTUR KALIMAT DAN MEREKOMENDASIKANYA MENGGUNAKAN ALGORITMA DAMERAU LEVENSHTEIN DISTANCE Prabowo, Budi Rustamadji, Heru Cahya Fauziah, Yuli Cocke Younger Kasami Damerau Levenshtein Distance Struktur Kalimat Kata Bahasa Indonesia Penggunaan kata baku dan struktur kalimat merupakan salah satu syarat dalam penulisan laporan penelitian, tanpa disadari kesalahan penulisan dapat terjadi baik berupa kesalahan pengetikan maupun pada struktur kalimat, beberapa penyebabnya ialah kebiasaan saat menulis pesan pendek, berkembangnya bahasa yang digunakan sehari-hari dan susunan keyboard yang terlalu dekat. Kesalahan penulisan biasanya akan segera diperbaiki setelah selesai menulis, namun untuk memperbaikinya diperlukan waktu dan ketelitian. Algoritma CYK merupakan algoritma parsing keanggotaan untuk tatabahasa bebas konteks yang dapat digunakan untuk memeriksa struktur kalimat sedangkan algoritma DLD merupakan algoritma yang mampu menghitung jarak perbedaan dari dua buah string sehingga dapat dimanfaatkan untuk rekomendasi kata dan kalimat. Tujuan dari penelitian ini adalah menerapkan algoritma CYK untuk mendeteksi struktur kalimat dan algoritma DLD untuk merekomendasikan kata dan struktur kalimat. Pemeriksaan kalimat dilakukan dengan mengelompokan setiap kata yang terdapat pada teks berdasarkan jenisnya, kata yang telah dikelompokkan tersebut kemudian disusun kembali kedalam bentuk kalimat dan diperiksa dengan algoritma CYK untuk mengetahui apakah kalimat tersebut benar atau salah, jika kalimat salah maka diberikan rekomendasi kalimat menggunakan algoritma DLD dengan menghitung edit distance-nya, selain perbaikan pada kalimat algoritma DLD juga melakukan perbaikan pada kata yang salah. Hasil pengujian didapatkan tingkat keberhasilan algoritma CYK dalam mendeteksi struktur kalimat sebesar 96% dan algoritma DLD dalam merekomendasikan kata sebesar 96%, sedangkan untuk merekomendasikan kalimat sebesar 88%. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3378 10.31315/telematika.v1i1.3378 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 111-119 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 111-119 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3378/2563 10.31315/telematika.v1i1.3378.g2563 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3379 2021-01-18T06:17:50Z telematika:AI driver

PEMANFAATAN TEXT MINING PADA SISTEM PENGOLAHAN SKRIPSI MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER DAN SIMPLE ADDITIVE WEIGHTING Sholihuda, Firna Sholihuda Yuwono, Bambang Rustamadji, Heru Cahya Text Mining Tokenizing Filltering Stemming Naïve Bayes Classifier Simple Additive Weighting Tahapan awal skripsi adalah pengajuan proposal skripsi. Proposal skripsi akan diproses untuk menentukan dosen pembimbing, kemudian skripsi dapat dilanjutkan ke tahap penyusunan. Saat ini pengolahan skripsi menggunakan cara manual, dari penentuan dosen pembimbing hingga pengumpulan laporan akhir. Koordinator Skripsi juga harus mencocokkan data proposal dengan data dosen pembimbing secara manual. Maka, penggunaan Sistem Informasi dapat membantu menentukan dosen pembimbing dan sebagai layanan skripsi. Langkah awal dalam menentukan dosen pembimbing adalah mengetahui tema dan konsentrasi proposal skripsi. Untuk mengetahui tema dan konsentrasi proposal dilakukan analisis isi proposal menggunakan metode Text Mining. Text Mining bekerja dengan cara preprocessing menggunakan tokenizing, filtering, dan stemming untuk mendapatkan kata dasar dari setiap kata dalam setiap kalimat. Kemudian melakukan klasifikasi dokumen proposal sesuai dengan tema dan konsentrasi menggunakan algoritma Naïve Bayes Classifier berdasarkan hasil preprocessing. Tema dan konsentrasi merupakan salah satu kriteria penentukan dosen pembimbing menggunakan algoritma Simple Additive Weighting untuk dilakukan perangkingan pembobotan setiap dosen. Berdasarkan hasil penelitian yang telah dilakukan, proses penentuan tema dan konsentrasi dari proposal skripsi mahasiswa dapat membantu dalam melakukan klasifikasi dokumen dengan tingkat akurasi mencapai 78%. Pembobotan dosen pembimbing proposal skripsi sesuai dengan kriteria menunjukkan hasil dengan nilai perangkingan yang beragam sesuai dengan bobot kriteria setiap dosen pembimbing. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3379 10.31315/telematika.v1i1.3379 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 120-130 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 120-130 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3379/2564 10.31315/telematika.v1i1.3379.g2564 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3380 2021-01-18T06:17:50Z telematika:AI driver

APLIKASI PENGENALAN PENUTUR PADA IDENTIFIKASI SUARA PENELEPON MENGGUNAKAN MEL-FREQUENCY CEPSTRAL COEFFICIENT DAN VECTOR QUANTIZATION (Studi Kasus : Layanan Hotline Universitas Pembangunan Nasional “Veteran” Yogyakarta) Rasyid, Muhammad Fahim Jayadianti, Herlina Sofyan, Herry Hotline Speaker Recognition Frekuensi Mel-Frequency Cepstral Coefficient (MFCC) Vector Quantization (VQ) Layanan hotline Universitas Pembangunan Nasional “Veteran” Yogyakarta merupakan layanan yang dapat digunakan oleh semua orang. Layanan tersebut digunakan dosen dan pegawai untuk berbagi informasi dengan bagian-bagian yang berlokasi di gedung rektorat. Penelepon dapat berkomunikasi dengan bagian yang dituju apabila telah teridentifikasi oleh petugas layanan hotline. Terminologi identitas yang terdiri dari nama, jabatan serta asal jurusan atau bagian ditanyakan saat proses identifikasi. Tidak terdapat catatan hasil identifikasi penelepon baik dalam bentuk fisik maupun basis data yang terekam pada komputer. Hal tersebut mengakibatkan tidak adanya dokumentasi yang dapat dijadikan barang bukti untuk menindak lanjuti kasus kesalahan identifikasi.  Penelitian ini fokus untuk mengurangi resiko kesalahan identifikasi penelepon menggunakan teknologi speaker recognition. Frekuensi suara diekstraksi menggunakan metode Mel-Frequency Cepstral Coefficient (MFCC) sehingga dihasilkan nilai Mel Frequency Cepstrum Coefficients. Nilai Mel Frequency Cepstrum Coefficients dari semua data latih suara  pegawai Universitas Pembangunan Nasional “Veteran” Yogyakarta kemudian dibandingkan dengan sinyal suara penelpon menggunakan metode Vector Quantization (VQ). Aplikasi pengenalan penutur mampu mengidentifikasi suara penelepon dengan tingkat akurasi 80% pada nilai ambang (threshold) 25. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3380 10.31315/telematika.v1i1.3380 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 68-86 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 68-86 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3380/2565 10.31315/telematika.v1i1.3380.g2565 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3381 2021-01-18T06:17:50Z telematika:RBT driver

SISTEM PENGAWASAN DAN PERINGATAN DINI KEBENCANAAN PADA GOA TERINTEGRASI MENGGUNAKAN IOT Rahmanda, Danang Arif Pratomo, Awang Hendrianto Simanjuntak, Oliver Samuel Smart City Internet of Things Pengawasan Peringatan Dini Gua Smart city merupakan sistem yang memberikan perkembangan pada kota yang digunakan dengan tujuan untuk lebih baik serta memberikan pelayanan terhadap masyarakat untuk memenuhi kehidupan yang layak. Peringatan dini atau Early Warning System (EWS) pada bidang lingkungan merupakan bagian dari lingkungan cerdas untuk memberikan sebuah peringatan dini suatu kejadian seperti kebencanaan yang diberitahukan kepada masyarakat. Penerapan sistem peringatan dini tersebut di terapkan pada lingkungan yang meliputi daerah wisata alam, salah satunya gua. Gua merupakan suatu lingkungan berupa bentukan akibat proses alam yang melubangi batuan. Dengan adanya sistem pengawasan dan peringatan dini saat ini yang merupakan sistem yang sangat dibutuhkan, mengingat bencana yang sering realtime terjadi dan terkadang yang tidak dapat diduga. Dari cara pengamatan dan pemberitahuan informasi yang lama mengenai keadaan didalam gua ini dapat dilakukan dengan cepat dengan data yang diperbaharui secara secara terus menerus. Sistem pengawasan yang dirancang dengan menggunakan sensor DHT11 Sebagai Sensor Kelembaban Udara, DS18 Sebagai Sensor Ruang Luar,BMP180 Sebagai Sensor Suhu Ruang Dalam dan Tekanan Udara, FC28 Sebagai Sensor Kelembaban Tanah, Rain Gaug Sebagai Sensor Curah Hujan. Data yang didapatkan dari masing-masing sensor akan dikirimkan kedalam database yang berada dalam cloud server, sehingga data akan terus diperbaharui. Hasil dari pengujian sensor didapatkan memiliki selisih yang tidak jauh dengan nilai nyata yang diuji dengan alat pengukur lain ketika daya atau tegangan yang diberikan pada sensor lebih tinggi. Pada tegangan 1 ampere untuk sensor suhu memberikan nilai 30 derajat selsius sedangkan dengan termometer adalah 32 derajat selsius, dan pada tegangan 5 ampere sensor suhu dan thermometer bernilai 29 derajat selsius diwaktu yang sama. Pada sensor kelembaban udara, dengan tegangan 1 ampere mendapatkan 63% sedangkan pada nilai nyatanya 65%, dan dengan tegangan 5 ampere, pada kelembaban nyata dan menggunakan sensor bernilai 77% diwaktu yang sama. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3381 10.31315/telematika.v1i1.3381 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 49-67 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 49-67 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3381/2566 10.31315/telematika.v1i1.3381.g2566 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3382 2021-01-18T06:17:51Z telematika:RBT driver

E-TOLL COLLECTION PADA SISTEM TRANSAKSI TOL TERTUTUP DENGAN METODE LAYANAN BERBASIS LOKASI STUDI KASUS PT JASA MARGA (PERSERO), TBK Isni, Rahmat Nur Santosa, Budi Simanjuntak, Oliver Samuel Digital Payment E-Toll Collection Location Based Service RSSI Ranging Trilateration Wifi Positioning System Jasa Marga (Persero) Tbk adalah Badan Usaha Milik Negara Indonesia yang bergerak dibidang penyelenggara jasa jalan tol. Beberapa permasalahan yang kerap muncul pada pelayanan transaksi dan pembayaran tol, diantaranya adalah pelayanan transaksi pada sistem tol tertutup yang belum bisa melayani sistem pembayaran secara tapless, masalah sistem transaksi uang elektronik, masalah antrian dan masalah polusi berupa limbah kertas dan polusi udara. E-Toll Collection merupakan aplikasi transaksi dan pembayaran tol menggunakan rekening digital berbasis server yang dapat membaca lokasi gerbang dan gardu transaksi pada sistem tol terbuka dan sistem tol tertutup. Metode yang digunakan dalam pencarian lokasi transaksi adalah trilateration dengan menggunakan nilai RSSI yang dikonversi menjadi jarak (meter) antara titik lokasi akses poin dengan user.Berdasarkan pengujian yang dilakukan pada gerbang tol Cikarang Utara, diperoleh hasil akurasi koordinat pembacaan lokasi gerbang dan gardu dengan rata-rata 92,7% dengan toleransi kesalahan sebear ±1 meter, hasil response time pada transaksi sistem tol terbuka dan tertutup diselesaikan dengan rata-rata 2 detik. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3382 10.31315/telematika.v1i1.3382 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 131-144 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 131-144 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3382/2567 10.31315/telematika.v1i1.3382.g2567 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3383 2021-01-18T06:17:51Z telematika:AI driver

OTOMATISASI LAYANAN FREQUENTLY ASK QUESTIONS BERBASIS NATURAL LANGUGAE PROCESSING PADA TELEGRAM BOT Husamuddin, Hani Prasetyo, Dessyanto Boedi Rustamadji, Heru Cahya Chatbot Natural Language Processing TensorFlow Telegram Kitabisa atau kitabisa.com adalah platform untuk menggalang dana dan berdonasi secara online terpopuler di Indonesia. Kitabisa.com menyediakan frequently ask questions (FAQ) untuk membantu visitor mengetahui mengenai Kitabisa.com dan bagaimana menggunakan layanan yang Kitabisa.com sediakan. Pada penelitian ini akan mengusulkan satu solusi untuk memaksimalkan otomatisasi layanan FAQ Kitabisa.com berbasis Natural Language Processing (NLP). Layanan ini dilakukan dengan fitur bot pada messenger Telegram yang dirancang berbasis NLP menggunakan teknologi TensorFlow. Dengan demikian, chatbot ini bertindak sebagai customer service yang akan menjawab pertanyaan-pertanyaan yang diajukan. Hasil dari penelitian ini adalah chatbot dengan menggunakan metode NLP dapat memberikan respon sesuai dengan konteks atas apa yang user tanyakan dengan akurasi 73%. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3383 10.31315/telematika.v1i1.3383 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 145-157 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 145-157 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3383/2568 10.31315/telematika.v1i1.3383.g2568 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3384 2021-01-18T06:17:51Z telematika:SE driver

PEMBERITAHUAN KETERLAMBATAN ANGSURAN MENGGUNAKAN SHORT MESSAGE SERVICE GATEWAY (STUDI KASUS KOPERASI SIMPAN PINJAM MAKMUR YOGYAKARTA) Wibowo, Jalu Satrio Sofyan, Herry Yuwono, Bambang Koperasi SMS Gateway Web PHP Javasript SMS Waterfall Perkembangan teknologi informasi di era globalisasi ini telah mengalami perubahan yang cukup pesat. Hal ini dapat  lihat dengan banyaknya perusahaan atau badan usaha atau instansi tidak lepas dari pengaruh teknologi informasi. Salah satunya adalah Koperasi simpan pinjam Makmur Yogyakarta sebagai badan usaha ekonomi rakyat yang bersifat sosial yang merupakan usaha bersama berdasarkan atas azas kekeluargaan. Setiap bentuk kegiatan dan usaha pada umumnya memiliki sebuah tujuan yang jelas sehingga dalam mengelola kegiatan koperasi oleh petugas harus memberikan kepercayaan dan memberikan pelayanan yang baik bagi anggota-anggota koperasi. Permasalahan dalam menjalankan kegiatan koperasi antara lain penunggakan dikarenakan keterlambatan pembayaran angsuran, kinerja petugas yang kurang optimal, keterlambatan dalam pemberitahuan informasi yang membuat pembayaran angsuran terhambat, dan pencatatan data dengan pembukuan lalu di memasukan data ke dalam Microsoft excel sehingga kurang terkomputerisasi dalam merekam data koperasi maka apabila dilakukan dengan cara seperti biasa mengecek data satu persatu maka memerlukan waktu yang cukup lama dalam mencari data anggota yang memiliki permasalahan data hilang  dalam mencari file data koperasi belum termasuk juga yang tidak ditemukan menyebabkan data kurang terekam dengan baik sehingga masih kurang efisien dan belum lagi masalah pemberitahuan yang kurang tersampaikan sehingga masih ada anggota yang menunggak pembayaran angsuran pada setiap bulannya menyebabkan pihak koperasi bekerja lebih terutama memberitahu perihal pembayaran dengan sms satu persatu kesetiap anggota yang menunggak dengan petugas yang masih kurang turut menjadi masalah kurang efisen. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3384 10.31315/telematika.v1i1.3384 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 158-170 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 158-170 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3384/2569 10.31315/telematika.v1i1.3384.g2569 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3620 2021-01-18T06:17:52Z telematika:SE driver

RANCANG BANGUN SISTEM INFORMASI PENGAJUAN KREDIT PADA BUMDESA BERSAMA SANTHI SEDANA Pande, Putu Risma Emiliana Putra, I Nyoman Tri Anindia Putri, Ni Wayan Suardiati System Credit BUM Desa BUM Desa Bersama Santhi Sedana merupakan badan usaha milik desa yang sebagian atau seluruh modalnya berasal dari desa. Dana yang dihimpun tersebut disalurkan lagi kepada masyarakat dalam bentuk kredit yang dapat memberikan keuntungan financial serta kesejahteraan masyarakat desa. Untuk masyarakat yang ingin mengajukan kredit harus datang ke kantor BUM Desa Santhi Sedana, tidak jarang masyarakat harus mendatangi kantor berulangkali untuk melengkapi berkas pengajuan kredit. Tujuan dilakukan penelitian ini adalah untuk membangun sistem informasi yang dapat memudahkan nasabah dalam mengajukan kredit dan membantu pegawai dalam mengelola data kredit nasabah. Sistem informasi kredit ini, dibangun dengan metode pengumpulan data yakni observasi, wawancara, dokumentasi, dan studi pustaka. Pengujian sistem dilakukan dengan black box testing dimana dari hasil pengujian, sistem yang dibangun mampu mengelola pengajuan kredit nasabah dan data pembayaran kredit nasabah. Jurusan Informatika 2020-11-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3620 10.31315/telematika.v17i2.3620 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 17 No. 2 (2020): Edisi Oktober 2020; 171-181 Telematika; Vol 17 No 2 (2020): Edisi Oktober 2020; 171-181 2460-9021 1829-667X 10.31315/telematika.v17i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3620/2884 10.31315/telematika.v17i2.3620.g2884 Copyright (c) 2020 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3931 2022-07-15T01:51:46Z telematika:GEN driver

Tahfidz Quran Monitoring System in Islamic Boarding Schools Marier, Syauqie Muhammad Dewi, Pipit Febriana islamic boarding schools tahfidz monitoring system tahfidz information system Purpose: development a good tahfidz quran monitoring system, in presenting the data to quran teachers and parents. Presentation of data in the proposed monitoring system is in the form of tables, text, a graph of the Tahfidz progression and a dashboard for the achievement of the Tahfidz target.Design/methodology/approach: waterfallFindings/result: the tahfidz monitoring system that presents data in the form of graphs, charts, tables and text, thus providing monitoring functions that are easy to read and quickly understood.Originality/value/state of the art: dashboard display and chart on the tahfidz quran monitoring system Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3931 10.31315/telematika.v18i1.3931 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 1-11 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 1-11 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3931/3340 10.31315/telematika.v18i1.3931.g3340 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/3968 2022-07-15T01:51:46Z telematika:GEN driver

The Determinant Analysis of the Utilization of Google Classroom as the E-Learning Facility in Yogyakarta Nahdlatul Ulama University Dewi, Pipit Febriana Abadi, Anis Susila E-learning Google Classroom Qualitative Purpose: to find out what factors cause lecturers and students to adopt and refuse to adopt Google Classroom as a means of E-Learning at the Yogyakarta Nahdlatul Ulama University.Design/methodology/approach: This research was conducted using a qualitative approach to get the meaning of a phenomenon. The Innovation Diffusion Theory is used as the basis for this research to find out how the role of Google Classroom as a means of E-Learning and how the suitability of Google Classroom as a means of E-Learning at Nahdlatul Ulama University Yogyakarta.Findings/result: the factors of adoption consisted of synchronizing the students and lecturers’ email with Google, integrating other Google features, making an efficiency of fund, time and place, finding an alternative way for e-learning, evaluating the facilities, filling the teaching and learning process, communicating between the lecturers and students, and knowing the lateness of submitting assignment. Besides, there were some factors of rejection such as the limited ownership of electronic media, limited knowledge, Internet connection, and no attendance facilityOriginality/value/state of the art: The factors of lecturers and students are adopt and refuse to adopt Google Classroom as a means of E-Learning at Nahdlatul Ulama University Yogyakarta. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3968 10.31315/telematika.v18i1.3968 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 12-26 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 12-26 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/3968/3341 10.31315/telematika.v18i1.3968.g3341 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4025 2022-07-15T01:51:46Z telematika:AI driver

VGG16 Transfer Learning Architecture for Salak Fruit Quality Classification Rismiyati, Rismiyati Luthfiarta, Ardytha salak transfer learning VGG16 deep learning Purpose: This study aims to differentiate the quality of salak fruit with machine learning. Salak is classified into two classes, good and bad class.Design/methodology/approach: The algorithm used in this research is transfer learning with the VGG16 architecture. Data set used in this research consist of 370 images of salak, 190 from good class and 180 from bad class. The image is preprocessed by resizing and normalizing pixel value in the image. Preprocessed images is split into 80% training data and 20% testing data. Training data is trained by using pretrained VGG16 model. The parameters that are changed during the training are epoch, momentum, and learning rate. The resulting model is then used for testing. The accuracy, precision and recall is monitored to determine the best model to classify the images.Findings/result: The highest accuracy obtained from this study is 95.83%. This accuracy is obtained by using a learning rate = 0.0001 and momentum 0.9. The precision and recall for this model is 97.2 and 94.6.Originality/value/state of the art: The use of transfer learning to classify salak which never been used before. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4025 10.31315/telematika.v18i1.4025 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 37-48 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 37-48 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4025/3344 10.31315/telematika.v18i1.4025.g3344 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4247 2022-07-15T01:51:46Z telematika:SE driver

Pencak Silat Tournament Information System Wardana, Ari Kusuma Aribowo, Eko information system pencak silat IPSI Purpose:This research was conducted to help manage the implementation of the pencak silat championship. So that the championship can run in an orderly and professional manner.Design/methodology/approach:This research went through several stages, starting from data collection, system requirements analysis, design, implementation, and system testing.Findings/result:Website-based information system for pencak silat tournament.Originality/value/state of the art:Pencak silat is a martial arts rich in techniques, benefits, and carries noble values that should be preserved as the Indonesian nation's successor. To preserve the existence of pencak silat in Indonesia, various pencak silat competitions were held in several cities in Indonesia. In the championship implementation, several things can disrupt the course of the matches. Of course, it will make the championship unprofessional. For this reason, along with the development of science and technology, a system was created that would help manage the implementation of the pencak silat championship so that the championship can run in an orderly and professional manner. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4247 10.31315/telematika.v18i1.4247 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 131-142 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 131-142 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4247/3351 10.31315/telematika.v18i1.4247.g3351 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4341 2022-07-15T01:51:46Z telematika:AI driver

Implementation Of Text Mining For Emotion Detection Using The Lexicon Method (Case Study: Tweets About Covid-19) Aribowo, Agus Sasmito Khomsah, Siti Covid-19 Emotion Analysis Lexicon Information and news about Covid-19 received various responses from social media users, including Twitter users. Changes in netizen opinion from time to time are interesting to analyze, especially about the patterns of public sentiment and emotions contained in these opinions. Sentiment and emotional conditions can illustrate the public's response to the Covid-19 pandemic in Indonesia. This research has two objectives, first to reveal the types of public emotions that emerged during the Covid-19 pandemic in Indonesia. Second, reveal the topics or words that appear most frequently in each emotion class. There are seven types of emotions to be detected, namely anger, fear, disgust, sadness, surprise, joy, and trust. The dataset used is Indonesian-language tweets, which were downloaded from April to August 2020. The method used for the extraction of emotional features is the lexicon-based method using the EmoLex dictionary. The result obtained is a monthly graph of public emotional conditions related to the Covid-19 pandemic in the dataset. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4341 10.31315/telematika.v18i1.4341 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 49-60 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 49-60 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4341/3345 10.31315/telematika.v18i1.4341.g3345 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4369 2022-07-15T01:51:47Z telematika:AI driver

Decision Support System For Determining The Type Of Workout Using The Fuzzy Analythical Hierarchy Process (F-AHP) In GYM STIKI Putra, I Nyoman Tri Anindia Kartini, Ketut Sepdyana Sinariyani, Ni Komang Ayu Maharani, Nia Workout F-AHP Decision Support System Purpose: Decision Support System for Determining the Type of Workout Using the Fuzzy Analythical Hierarchy Process (F-AHP) Method The STIKI GYM was created to make it easier for trainers to provide training for STIKI GYM participants who carry out workouts at STIKI GYM. Meanwhile, for STIKI GYM participants, the system can make it easier to carry out workout activities according to their respective body loads.Design/methodology/approach: Fuzzy Analythical Hierarchy Process (F-AHP) Method and being tested with black box testingFindings/result: Users can find out workout activities by entering the criteria for body weight, height, and exercise intensity into the system and helping trainers provide training in accordance with the recommendations for workout activities from the Decision Support System for Determining the Types of Workout Using the Fuzzy Analythical Hierarchy Process (F-AHP) Method at STIKI GYM.Originality/value/state of the art: The Decision Support System for determining the Type of Workout is indeed implemented at STIKI GYM by using data support in the form of interview results and participant data from STIKI GYM. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4369 10.31315/telematika.v18i1.4369 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 73-87 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 73-87 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4369/3347 10.31315/telematika.v18i1.4369.g3347 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4493 2022-07-15T01:51:47Z telematika:AI driver

Sentiment Analysis On YouTube Comments Using Word2Vec and Random Forest Khomsah, Siti youtube comments sentiment analysis word2vec skip-gram random forest Purpose: This study aims to determine the accuracy of sentiment classification using the Random-Forest, and Word2Vec Skip-gram used for features extraction. Word2Vec is one of the effective methods that represent aspects of word meaning and, it helps to improve sentiment classification accuracy.Methodology: The research data consists of 31947 comments downloaded from the YouTube channel for the 2019 presidential election debate. The dataset consists of 23612 positive comments and 8335 negative comments. To avoid bias, we balance the amount of positive and negative data using oversampling. We use Skip-gram to extract features word. The Skip-gram will produce several features around the word the context (input word). Each of these features contains a weight. The feature weight of each comment is calculated by an average-based approach. Random Forest is used to building a sentiment classification model. Experiments were carried out several times with different epoch and window parameters. The performance of each model experiment was measured by cross-validation.Result: Experiments using epochs 1, 5, and 20 and window sizes of 3, 5, and 10, obtain the average accuracy of the model is 90.1% to 91%. However, the results of testing reach an accuracy between 88.77% and 89.05%. But accuracy of the model little bit lower than the accuracy model also was not significant. In the next experiment, it recommended using the number of epochs and the window size greater than twenty epochs and ten windows, so that accuracy increasing significantly.Value: The number of epoch and window sizes on the Skip-Gram affect accuracy. More and more epoch and window sizes affect increasing the accuracy. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4493 10.31315/telematika.v18i1.4493 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 61-72 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 61-72 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4493/3346 10.31315/telematika.v18i1.4493.g3346 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4495 2022-07-15T01:51:47Z telematika:AI driver

Good Morning to Good Night Greeting Classification Using Mel Frequency Cepstral Coefficient (MFCC) Feature Extraction and Frame Feature Selection Heriyanto, Heriyanto extraction of features features frames cepstral coefficient linear Purpose:Select the right features on the frame for good accuracyDesign/methodology/approach:Extraction of Mel Frequency Cepstral Coefficient (MFCC) Features and Selection of Dominant Weight Normalized (DWN) FeaturesFindings/result:The accuracy results show that the MFCC method with the 9th frame selection has a higher accuracy rate of 85% compared to other frames.Originality/value/state of the art:Selection of the appropriate features on the frame. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4495 10.31315/telematika.v18i1.4495 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 88-105 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 88-105 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4495/3348 10.31315/telematika.v18i1.4495.g3348 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4586 2022-07-15T01:51:47Z telematika:AI driver

Prediction Of Drug Sales Using Methods Forecasting Double Exponential Smoothing (Case Study : Hospital Pharmacy of Condong Catur) Sabarina, Annesa Maya Rustamaji, Heru Cahya Himawan, Hidayatulah Sales Prediction Pharmacies Double Exponential Smoothing Alpha Purpose: Knowing the best alpha value from the data for each type of drug with various alpha parameters in the Double Exponential Smoothing Method and knowing the prediction results on each type of drug data at the Condong Catur Hospital pharmacy.Design/methodology/approach: Applying the Double Exponential Smoothing method with alpha parameters 0.1; 0.2; 0.3; 0.4; 0.5; 0.6; 0.7; 0.8; 0.9Findings/result: The test results on a system built using test data show that the double exponential smoothing method provides accuracy below 20% by producing a different Alpha (α) for each type of drug because the trend patterns in each drug sale are different at the Pharmacy at the Condong Catur Hospital. .Originality/value/state of the art: Based on previous research, this study has similar characteristics such as themes, parameters and methods used. Previous researchers used smoothing methods such as Double Exponential Smoothing in predicting stock / sales of goods  Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4586 10.31315/telematika.v18i1.4586 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 106-117 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 106-117 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4586/3349 10.31315/telematika.v18i1.4586.g3349 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4587 2022-07-15T01:51:47Z telematika:AI driver

Classification of Anemia with Digital Images of Nails and Palms using the Naive Bayes Method Peksi, Nandha Juniaroesita Yuwono, Bambang Florestiyanto, Mangaras Yanu anemia classification naive bayes Purpose: Early detection of anemia based on nails and palms images by applying the Naive Bayes method, as well as to measure the level of accuracy in detecting anemia.Design/methodology/approach: Using the Naive Bayes method. System development uses the waterfall method.Findings/result: Based on the results of the tests that have been carried out, the resulting accuracy is 87.5% with varying light intensities and is 92.3% by using a light intensity of 5362 Lux.Originality/value/state of the art: The difference between this study and previous research is in the image pre-processing method and classification method. In this study, the images of the nails and palms were converted to the YCbCr color space to be segmented and color features extracted. Then the color features will be classified using the Naive Bayes classification method. The output of this system is the result of the input image classification, whether normal or anemic. Jurusan Informatika 2021-03-16 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4587 10.31315/telematika.v18i1.4587 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 1 (2021): Edisi Februari 2021; 118-130 Telematika; Vol 18 No 1 (2021): Edisi Februari 2021; 118-130 2460-9021 1829-667X 10.31315/telematika.v18i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4587/3350 10.31315/telematika.v18i1.4587.g3350 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4664 2022-07-15T01:51:44Z telematika:AI driver

Implementation of Fuzzy Multi-Objective Optimization On The Basic Of Ratio Analysis (Fuzzy-MOORA) In Determining The Eligibility Of Employee Salary Sudipa, I Gede Iwan Putra, I Nyoman Tri Anindia Asana, Dwi Putra Hanza, Revan Dwi Decision Making Employee Salary Bonuses Fuzzy MOORA Purpose: CV. Harmoni Permata has several employees, and each employee has a bonus salary. However, in determining who is eligible for the employee salary bonus at CV. Harmoni Permata is still done manually assessment. This causes an error in the calculation because the decision-maker must look at previous historical data to decide.Design/methodology/approach: System design includes systems that can manage user data, position data, criteria data, criteria description data, absences data, task data, and assessment data, which will produce an assessment report. The MOORA method approach is used because it has calculations with minimum and simple math and has a good level of selectivity. Findings/result: The normalization comparison test of the manual calculation of the MOORA method with the system calculation results is the same, with the best five alternative employees who deserve a salary bonus.Originality/value/state of the art: Based on previous research reviews, this study uses the criteria for performance, honesty, attendance, and accuracy by determining the weight based on the type of benefit or cost and the MOORA method in calculating the final value of alternative ranking. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4664 10.31315/telematika.v18i2.4664 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 143-156 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 143-156 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4664/3827 10.31315/telematika.v18i2.4664.g3827 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4786 2022-07-15T01:51:44Z telematika:AI driver

Cluster Analysis of Hospital Inpatient Service Efficiency Based on BOR, BTO, TOI, AvLOS Indicators using Agglomerative Hierarchical Clustering Fahrudin, Tresna Maulana Riyantoko, Prismahardi Aji Hindrayani, Kartika Maulida Swari, Made Hanindia Prami cluster analysis hospital inpatient agglomerative hierarchical clustering silhouette coefficient Purpose: The research proposed an approach for grouping hospital inpatient service efficiency that have the same characteristics into certain clusters based on BOR, BTO, TOI, and AvLOS indicators using Agglomerative Hierarchical Clustering.Design/methodology/approach: Applying Agglomerative Hierarchical Clustering with dissimilarity measures such as single linkage, complete linkage, average linkage, and ward linkage.Findings/result: The experiment result has shown that ward linkage was given a quite good score of silhouette coefficient reached 0.4454 for the evaluation of cluster quality. The cluster formed using ward linkage was more proportional than the other dissimilarity measures. Ward linkage has generated cluster 0 consists of 23 members, cluster 1 consists of 34 members, while both of cluster 2 and 3 consists of only 1 member respectively. The experiment reported that each cluster had problems with inpatient indicators that were not ideal and even exceeded the ideal limit, but cluster 0 generated the ideal BOR and TOI parameters, both reached 52.17% (12 of 23 hospital inpatient) and 78.36% (18 of 23 hospital inpatient) respectively.Originality/value/state of the art: Based on previous research, this study provides an alternative to produce more proportional, representative and quality clusters in mapping hospital inpatient service efficiency that have the same characteristics into certain clusters using Agglomerative Hierarchical Clustering Method compared to the K-means Clustering Method which is often trapped in local optima.  Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4786 10.31315/telematika.v18i2.4786 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 194-210 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 194-210 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4786/3952 10.31315/telematika.v18i2.4786.g3952 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4823 2022-07-15T01:51:44Z telematika:AI driver

Implementation of Convolutional Neural Network (CNN) in Facial Expression Recognition Seandrio, Augyeris Lioga Pratomo, Awang Hendrianto Florestiyanto, Mangaras Yanu Ekspresi Wajah Klasifikasi Deep Learning Convolutional Neural Network. Tujuan: Membantu pengajar melakukan monitoring emosi siswa dengan menerapkan metode Convolutional Neural Network pada aplikasi, serta mengetahui akurasi dalam melakukan pengenalan ekspresi wajah.Perancangan/metode/pendekatan: Menggunakan Convolutional Neural Network untuk mengklasifikasi pengolahan berupa citra. Pengembangan sistem menggunakan metode prototype.Hasil: Berdasarkan hasil pengujian yang dilakukan dengan menggunakan 3589 data ekspresi dasar manusia mendapatkan nilai akurasi sebesar 70,46%, nilai presisi sebesar 71% dan nilai recall sebesar 70%.Keaslian/ state of the art: Berdasarkan penelitian sebelumnya, penelitian ini mempunyai karakteristik yang relatif serupa dalam tema penelitian. Namun memiliki perbedaan pada metode penelitan, perangkat yang digunakan, dan hasil keluaran penelitian.Pada penelitian sebelumnya, dengan objek yang sama yaitu wajah dan emosi wajah, pada metode yang digunakan, perangkat dalam pengambilan citra emosi dan wajah, serta langkah-langkah dalam prosesnya pun berbeda. Pada penelitian ini emosi pada wajah diidentifikasi melalui citra yang diambil secara real-time menggunakan kamera dan dengan menerapkan metode Convolutional Neural Network dengan arsitektur visual group geometry (VGG) dengan 11, 13, 16 dan 19 lapisan yang akan menghasilkan probabilitas ekspresi dalam 7 ekspresi dasar manusia beserta kategorinya. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4823 10.31315/telematika.v18i2.4823 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 211-221 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 211-221 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4823/3833 10.31315/telematika.v18i2.4823.g3833 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/4844 2022-07-15T01:51:44Z telematika:SE driver

Development Of Executive Information Systems Of Cirebon City Government (Case Study: Department Of Communication, Informatics And Statistics) Alvianto, Muhammad Nur Hendra Sofyan, Herry Juwairiah, Juwairiah Executive Information Systems Dill Down GRAPPLE Purpose: Developing an executive information system to meet the information needs of the Mayor, Deputy Mayor, Regional Secretary and the heads of SKPD within the Cirebon City Government.Design / method / approach: Using the drill down method for solving information on executive information systems and the GRAPPLE system development methodResult: The development of an executive information system in Cirebon city government has assisted the executive, consisting of mayors, deputy mayors and regional secretaries and middle executives consisting of skpd within the Cirebon city government. Cirebon city government executive information system consists of five sectors in the city of Cirebon, namely economy, health, population, education and government. The results of the validation testing are 100% and the average user acceptance testing results are 85.29%.Authenticity / state of the art: Based on previous research, this study has the same characteristics but in the development of executive information systems it has differences in objects and methods of software development. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4844 10.31315/telematika.v18i2.4844 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 169-180 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 169-180 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/4844/3828 10.31315/telematika.v18i2.4844.g3828 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5067 2022-07-15T01:51:45Z telematika:AI driver

Data Mining for Determining The Best Cluster Of Student Instagram Account As New Student Admission Influencer Abdullah, Ahmad Irfan Priadana, Adri Muhajir, Muhajir Nur, Syahrir Nawir data mining Instagram account new student admission influencer the best cluster Purpose: This study aims to apply the web data extraction method to extract student Instagram account data and the K-Means data mining method to perform clustering automatically to determine the best cluster of students' Instagram accounts as influencers for new student admissions.Design/methodology/approach: This study implemented the web data extraction method to extract student Instagram account data. This study also implemented a data mining method called K-Means to cluster data and the Silhouette Coefficient method to determine the best number of clusters.Findings/result: This study has succeeded in determining the seven best student accounts from 100 accounts that can be used as influencers for new student admissions with the highest Silhouette Score for the number of influencers selected between 5-10, which is 0.608 of the 22 clusters.Originality/value/state of the art: Research related to the determination of the best cluster of students' Instagram accounts as new student admissions influencers using web data extraction and K-Means has never been done in previous studies. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5067 10.31315/telematika.v18i2.5067 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 255-266 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 255-266 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5067/3840 10.31315/telematika.v18i2.5067.g3840 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5316 2022-07-15T01:51:45Z telematika:GEN driver

Evaluation Of Jogja Application Success From User's Perspective Using Development of Delone And Mclean Models To Support The Realization Of The Smart Province Putri, Angelica Amartya Jayadianti, Herlina Yuwono, Bambang Delone and Mclean model Jogja Istimewa Success Evaluation SEM Purpose: This study aims to measure success and determine the factors that support or hinder the success of the Jogja Istimewa application.Methodology: This study uses a modified DeLone and McLean Model 2003. The data used are primary data obtained from interviews with the DISKOMINFO and answers to 125 users of the Jogja Istimewa application as respondents in a distributed questionnaire. The results of the questionnaire were processed using SPSS to test the validity, reliability and normality of the data. After that, the data is processed using Structural Equation Modeling (SEM) to test the inner model and outer model which includes hypothesis testing.Result There are nine hypotheses tested using the SEM model. Nine hypotheses were proposed, it was stated that five hypotheses were accepted and four other hypotheses were rejected. the Jogja Istimewa application has a high success rate. The factors that are stated to influence the success of the Jogja Istimewa application are Information Quality, Service Quality, System Quality and User Satisfaction. The factors that are stated to hinder the success of the Jogja Istimewa application are Format of Output and Reliability in the Information Quality variable, the System Quality variable in the Language indicator, and the Charges for System Use indicator on the Intention to Use variable.Value: Based on previous research, this study has a fairly similar reference but different case studies, indicators, and conceptual models to test hypotheses in addition to knowing the factors that hinder and support the success of the Jogja Istimewa application. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5316 10.31315/telematika.v18i2.5316 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 181-193 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 181-193 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5316/3830 10.31315/telematika.v18i2.5316.g3830 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5445 2023-03-04T07:02:46Z telematika:GEN driver

Smart Farming Optimization of Phalaenopsis Orchids Growth By Utilizing Fuzzy Logic Control on IoT Architecture Apriyani, Meyti Eka Prasetyo, Arief Aldila, Nurhidayat Tujuan: membangun sistem smart farming yang mampu memonitoring dan mengontrol kondisi serta perawatan terhadap tanaman secara otomatis. Penggunaan website sebagai monitoring dan sistem kontrol mikrokontroller secara realtime. Penyajian data dashboard dengan angka, tabel, dan grafik bergerak.Perancangan/metode/pendekatan: metode fuzzy sugenoHasil: sistem dapat bekerja secara otomatis maupun manual. Data yang dibaca dapat tampil secara realtime pada website dashboard. Sistem mampu mengkondisikan greenhouse sesuai dengan kondisi asli dari pembudidaya.Keaslian/ state of the art: penggunaan aplikasi dalam bentuk website yang dibuat sendiri dengan penyajian data-data secara realtime dalam bentuk angka, tabel, maupun grafik bergerak. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5445 10.31315/telematika.v19i1.5445 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 1-18 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 1-18 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5445/4424 10.31315/telematika.v19i1.5445.g4424 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5453 2022-07-15T01:51:42Z telematika:WS driver

The Design of an Android-Based Integrated Islamic Boarding School Information System as an Impact of Covid-19 Marier, Syauqie Muhammad Abadi, Anis Susila integration system islamic boarding school REST API Purpose: This study aims so that all information that is spread through various information systems in Islamic boarding schools can be known through an integrated systemDesign/methodology/approach: The method of developing the system using the prototype methodFindings/result: Android-based integrated information systemOriginality/value/state of the art: System integration in Islamic boarding schools that is carried out is the integration process of various systems that previously existed Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5453 10.31315/telematika.v18i3.5453 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 323-333 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 323-333 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5453/4265 10.31315/telematika.v18i3.5453.g4265 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5454 2022-07-15T01:51:45Z telematika:GEN driver

Backpropagation with BFGS Optimizer for Covid-19 Prediction Cases in Surabaya Fitriah, Zuraidah Tuloli, Mohamad Handri Anam, Syaiful Hidayat, Noor Yanti, Indah Mahanani, Dwi Mifta Covid-19 Surabaya prediction backpropagation BFGS Covid-19 is a new type of corona virus called SARS-CoV-2. One of the cities that has contributed the most to infected Covid-19 cases in Indonesia is Surabaya, East Java. Predicting the Covid-19 is the important thing to do. One of the prediction methods is Artificial Neural Network (ANN). The backpropagation algorithm is one of the ANN methods that has been successfully used in various fields. However, the performance of backpropagation is depended on the architecture and optimization method. The standard backpropagation algorithm is optimized by gradient descent method. The Broyden - Fletcher - Goldfarb - Shanno (BFGS) algorithm works faster then gradient descent. This paper was predicting the Covid-19 cases in Surabaya using backpropagation with BFGS. Several scenarios of backpropagation parameters were also tested to produce optimal performance. The proposed method gives better results with a faster convergence then the standard backpropagation algorithm for predicting the Covid-19 cases in Surabaya. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5454 10.31315/telematika.v18i2.5454 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 157-168 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 157-168 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5454/3826 10.31315/telematika.v18i2.5454.g3826 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5463 2022-07-15T01:51:43Z telematika:SE driver

Geographic Information System Design for Bridge Management in Brebes Regency Badruzzaman, Abdulloh Hendriana, Yana Bridges Brebes Regency Management Geographic Information System Purpose: geographic information system (GIS) design to monitoring and management of bridges that have geographic references, as well as a tool for planning activity programs (maintenance, rehabilitation, strengthening or replacement) of bridges.Design/methodology/approach: waterfallFindings/result: web-based geographic information system (GIS) for bridge management in Brebes RegencyOriginality/value/state of the art: this research does not only focus on site search as the main strength of GIS but maximizes bridge inspection activities as an important part of the bridge management system as a tool for planning bridge construction and maintenance activities Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5463 10.31315/telematika.v18i3.5463 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 384-400 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 384-400 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5463/4267 10.31315/telematika.v18i3.5463.g4267 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5475 2022-07-15T06:09:34Z telematika:GEN driver

Perancangan E-Government Pelayanan Pengaduan Dan Penyelesaian Sengketa Lingkungan di Era Kebiasaan Baru Pada Dinas Lingkungan Hidup Kota Makassar Akhriana, Asmah Faizal, Faizal Irmayana, Andi E-Government Web Sengketa Lingkungan Android At the Environmental Service, there is a PPLH Arrangement and Compliance Division. One of the environmental dispute reporting services is a dispute between two or more parties arising from activities that have the potential and or have an impact on the environment. The environmental complaint and dispute resolution service at the Makassar City Environmental Service have guidelines for verifying disputes involving many aspects of activities and data collection. The background of the research is the community's obstacles in quick access to reporting complaints due to allegations of pollution and or environmental destruction. Another problem is that the Department of the Environment still needs to prepare a verification plan for environmental disputes involving the reporter and related agencies. The impact of the pandemic that cities and even countries have felt makes the problem even more complicated. The research objective is to design an E-Government application for Complaints and Environmental Dispute Resolution Services that can be accessed by the public anytime and anywhere, especially in the era of new habits. The waterfall's system development method starts from system engineering, needs analysis, design, coding, testing and maintenance. Black box testing method for functional testing. The programming language used is the PHP programming language in building environmental dispute verification media and Android-based applications as a complaint medium. The results of this study are that this application can be a medium so that complaints become easier and can neatly document the dispute resolution process. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5475 10.31315/telematika.v19i1.5475 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 19-30 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 19-30 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5475/4419 10.31315/telematika.v19i1.5475.g4419 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5483 2022-07-15T01:51:43Z telematika:SE driver

Sistem Informasi Manajemen Notulen (E-RISALAH) Konversi Voice to Text Darwanto, Darwanto Saputra, Nurirwan Wardana, Ari Kusuma sistem informasi risalah rapat speech recognition Tujuan:Penelitian ini dilakukan untuk membantu notulis merisalahkan hasil rapat atau pertemuan dari suara menjadi tulisan. Sehingga kerja notulis lebih ringan dan menjaga kesehatan pendengaran. Perancangan/metode/pendekatan:Penelitian ini melalui beberapa tahap, yaitu perencaaan (planning), analisis (analysis), perancangan (design), dan implementasi (implementation). Hasil:Sistem Informasi Manajemen Notulen (E-RISALAH) Konversi Voice to Text berbasis website. Keaslian/state of the art:Risalah rapat adalah kegiatan mencatat atau menyalin seluruh hasil dari pertemuan. Dalam pelaksaan masih dikerjakan secara manual, dengan mendengarkan rekaman dan menyalin atau diketik secara manual, selain kurang efektif penggunaan headset dalam waktu yang lama dapat menggangu kesehatan pendengaran. Seiring perkembangan ilmu dan teknologi, maka dibuatlah sebuah sistem yang akan membantu merisalahkan hasil rapat dari suara menjadi tulisan. Dengan teknologi speech recognition dimana ini adalah sebuah kemampuan yang dimiliki oleh mesin atau aplikasi untuk mengindentifikasi kata dan frasa yang terdapat dalam bahasa lisan. Sehingga kerja notulis lebih ringan dan menjaga kesehatan pendengaran. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5483 10.31315/telematika.v18i3.5483 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 267-281 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 267-281 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5483/4248 10.31315/telematika.v18i3.5483.g4248 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5506 2022-07-15T01:51:45Z telematika:GEN driver

Automated Website Monitoring System Using Web Scraping and Raspberry Pi Arhandi, Putra Prima Mashudi, Irsyad Arief Nugroho, Fuad Adi automation website monitoring website availability Purpose: Create a system to monitor website availability automatically using web scraping and raspberry piDesign/methodology/approach: This system successfully checks website availability using various ISPs with an accuracy of more than 90%.Findings/result: This system successfully checks website availability using various ISPs with an accuracy of more than 90%.Originality/value/state of the art: The contribution of this research is to create systems and agents that collaborate automatically to check website availability. Tujuan: Membuat sebuah sistem untuk melakukan pemantauan ketersediaan situs web secara otomatis menggunakan web scraping dan raspberyy piPerancangan/metode/pendekatan: Pada penelitian ini dibuat sebuah sistem utama sebagai pusat data dan beberapa agent menggunakan raspberry pi. Sistem utama dibangun menggunakan codeigniter dan web scraping di raspberry pi dilakukan menggunakan node js serta REST API untuk komunikasi antara agent dan sistem utama.Hasil: Sistem ini berhasil melakukan pengecekan ketersediaan situs web menggunakan berbagai ISP dengan keakuratan lebih dari 90%.Keaslian/ state of the art: Kontribusi penelitian ini adalah membuat sistem dan agen yang berkolaborasi secara otomatis untuk mengecek ketersediaan situs web.  Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5506 10.31315/telematika.v18i2.5506 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 222-230 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 222-230 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5506/3834 10.31315/telematika.v18i2.5506.g3834 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5507 2022-07-15T01:51:45Z telematika:SE driver

Development of a Group Decision Support System with the Multi-Stage Multi-Attribute Group Decision Making (MS-MAGDM) Method on the Intelligent Warehouse Management System Nugroho, Simon Pulung group decision support system multi-stage decision making Hybrid Weight Averaging (HWA) Time Weight Averaging (TWA) Purpose: to find a solution with MS-DAGDM for the problem of different criteria used by decision maker at each stage.Design/methodology/approach: This research was conducted using literature review with a study of the theory of decision-making methods, group decisions, suplier selection processes, and factors that influence decisions in the context of warehousing and MS-MAGDM to solve the problems.Findings/result: This research find that GDSS prototypes which have four methods in making decisions. First, Analytical Hierarchy Process for weighting the division head level. Second, TOPSIS for divison head level decisions. Third, Hybrid Weight Averaging (HWA) manager level. Fourth, Time Weight Averaging (TWA) for manager level decisions.Originality/value/state of the art:The decision-making model of the GDSS system in this study combines four methods at each level of management. The section head level uses AHP for the level weighting and TOPSIS for decision making. Level managers use Hybrid Weight Averaging (HWA) weighting and Time Weight Averaging (TWA) for decisions. The combination of these methods is carried out using a Poisson distribution, for HWA and TWA operators to combine individual decisions into group decisions. Tujuan: Fokus penelitian ini adalah mencari solusi dengan MS-MAGDM untuk permasalahan perbedaan kriteria yang dipergunakan pembuat keputusan dalam setiap stage.Perancangan/metode/pendekatan: Metode yang digunakan yaitu kajian kepustakaan dengan kajian terhadap teori metode pembuatan keputusan, keputusan kelompok, proses pemilihan supplier, dan faktor yang berpengaruh pada keputusan dalam konteks pergudangan serta MS-MAGDM untuk menyelesaikan permasalahan tersebut.Hasil: Hasil penelitian ini berupa purwarupa GDSS yang memiliki 4 metode dalam pembuatan keputusan yaitu Analytical Hierarchi Process (AHP) untuk pembobotan level kepala bagian, TOPSIS untuk keputusan level kepala bagian, Hybrid Weight Averaging (HWA) pembobotan pada level manager dan Time Weight Averaging (TWA) untuk keputusan level managerKeaslian/ state of the art:Model pengambilan keputusan sistem GDSS penelitian ini menggabungkan 4 metode pada setiap tingkatan manajemen. Level kepala bagian menggunakan AHP untuk pembobotan level dan TOPSIS untuk pembuatan keputusan. Level manager menggunakan Hybrid Weight Averaging (HWA) pembobotan dan Time Weight Averaging (TWA) untuk keputusan. Penggabungan metode dilakukan menggunakan distribusi Poisson, untuk operator HWA dan TWA guna memadukan keputusan individu mejadi keputusan kelompok. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5507 10.31315/telematika.v18i2.5507 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 231-243 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 231-243 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5507/3835 10.31315/telematika.v18i2.5507.g3835 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5508 2022-07-15T01:51:45Z telematika:AI driver

Content Based Image Retrieval Using Gray Level Co-Occurrence Matrix to Detect Pneumonia in X-Ray Thorax Image Kaswidjanti, Wilis Yuwono, Bambang Azizah, Nisa’ul Cahyana, Nur Heri Pneumonia Image Processing CBIR GLCM Euclidean Distance Purpose:This study aims to detect the presence of pneumonia or not in thorax x-ray images using the Gray Level Co-Occurence Matrix (GLCM) method as well as find out the accuracy of the accuracy of pneumonia detection accuracy.Design/methodology/approach:The process of detecting pneumonia in thorax x-ray images can use Content Based Image Retriveal (CBIR). CBIR is an image search method by comparing the input image feature with the image feature in the database. Extraction features x-ray texture of thorax in pneumonia detection using Color Histogram, Discrete Cosine Transform and Gray Level Cooccurence Matrix (GLCM). From the day of extraction the feature will be carried out similarity measurements with database images using Euclidean Distance..Findings/result: The test results showed that the GLCM extraction feature with euclidean distance similarity measurements gained 95% accuracy on 100 training data and 20 test data, with the number of images displayed 6. Whereas when testing using data that has been trained produces 100% accuracy.Originality/value/state of the art:The difference between this study and previous research is in the pre-processing method section of imagery. This pre-processing process, x-ray image of thorax is carried out color histogram and discrete cosine transform process. Then continued the extraction of features using GLCM. The output of this system is the result of detection whether normal or pneumonia. Tujuan:Penelitian ini bertujuan untuk mendeteksi adanya Pneumonia atau tidak pada citra x-ray thorax menggunakan metode Gray Level Co-Occurence Matrix (GLCM) serta mengetahui akurasi tingkat akurasi deteksi pneumonia.Perancangan/metode/pendekatan:Proses deteksi penyakit Pneumonia pada citra x-ray thorax dapat menggunakan Content Based Image Retriveal (CBIR). CBIR adalah suatu metode pencarian citra dengan melakukan perbandingan antara fitur citra input dengan fitur citra yang ada didalam database. Ekstraksi  fitur tekstur x-ray thorax dalam deteksi pneumonia menggunakan Color Histogram, Discrete Cosine Transform dan Gray Level Cooccurence Matrix (GLCM). Dari hari ekstraksi fitur tersebut akan dilakukan pengukuran kemiripan dengan citra database menggunakan jarak Euclidean Distance.Hasil:Hasil pengujian menunjukkan bahwa fitur ekstraksi GLCM dengan pengukuran kemiripan Euclidean Distance diperoleh akurasi sebesar 95% pada data latih 100 dan data uji 20, dengan jumlah citra yang ditampilkan 6. Sedangkan bila pengujian menggunakan data yang sudah dilatihkan menghasilkan akurasi 100%.State of the art:Perbedaan penelitian ini dengan penelitian sebelumnya adalah pada bagian metode pre processing citra. Proses pre processing  ini,  citra x-ray thorax di lakukan proses Color Histogram dan Discrete Cosine Transform. Kemudian dilanjutkan ekstraksi fitur menggunakan GLCM. Output dari sistem ini berupa hasil deteksi apakah normal atau pneumonia. Jurusan Informatika 2021-10-04 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5508 10.31315/telematika.v18i2.5508 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 2 (2021): Edisi Juni 2021; 244-254 Telematika; Vol 18 No 2 (2021): Edisi Juni 2021; 244-254 2460-9021 1829-667X 10.31315/telematika.v18i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5508/3839 10.31315/telematika.v18i2.5508.g3839 Copyright (c) 2021 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5541 2022-07-15T01:51:43Z telematika:AI driver

Implementation of Deep Learning for Classification Type of Orange Using The Method Convolutional Neural Network Denata, Irvan Rismawan, Tedy Ruslianto, Ikhwan convolutional neural network orange deep learning alexnet Orange is a type of fruit that is easily found in Sambas Regency. The types that are widely sold are Siam oranges, madu susu and susu. Each type of orange has a different quality and a different price. The price difference often results in fraud committed by traders against buyers to the detriment of the buyer. This is because differentiating types of oranges based on the appearance of the fruit does not have a standard. Therefore, in this study, a citrus fruit classification system was created based on images by implementing deep learning. The method of deep learning used in this research is Convolutional Neural Network (CNN) with AlexNet architecture. The types of oranges that will be observed are madu oranges, madu susu, and siam. The data used are 2250 images of oranges with each class totaling 750 images with a size of 227x227 pixels. The training data is 1575 images and the test data is 675 images. The training is carried out with a total of 10 epochs and each epoch will produce a model. System testing is carried out based on the model generated in the training process. Each model will be observed results in the form of accuracy which is calculated using a confusion matrix. The most optimal model was generated from training in epoch the 9th which resulted in an accuracy of 94.81%. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5541 10.31315/telematika.v18i3.5541 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 297-307 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 297-307 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5541/4249 10.31315/telematika.v18i3.5541.g4249 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5542 2022-07-15T01:51:43Z telematika:SE driver

Multimedia Mobile Application of National Heroes History Learning for Children's Character Education ABADI, ANIS SUSILA DEWI, PIPIT FEBRIANA mobile aplication multimedia learning aplication national hero Purpose: develope a multimedia application about the history of national heroes from Indonesia.Design/methodology/approach: the method used is the UCD (User Centered Design) method.Findings/result: this multimedia mobile application of national heroes history learning for children's character education has succeeded in meeting user needs.Originality/value/state of the art: a multimedia application about the history of national heroes from Indonesia. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5542 10.31315/telematika.v18i3.5542 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 308-322 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 308-322 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5542/4266 10.31315/telematika.v18i3.5542.g4266 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/5569 2022-07-15T01:51:43Z telematika:GEN driver

Learning and Playing in Early Childhood with Augmented Reality Technology Purba, Doni El Rezen Silitonga, Parasian Augmented Reality Childhood Learning and Playing Game Education Purpose: Helping the learning process in early childhood through playing and learning activities with Augmented Reality technology.Design/methodology/approach: Using Augmented Reality technology with the Iterative Rapid Paper Prototype system development methodFindings/result: Based on tests conducted on 5 types of android devices, 10 samples of early childhood participants (4-5 years) and 5 groups of objects consisting of 10 types resulted in an increase in learning ability of 33.35% which was sourced from the measurement of the correct answers that were successfully obtained. between learning methods through pictures and learning using Augmented Reality technologyOriginality/value/state of the art: In previous research, the learning model was carried out on elementary school children (aged 6 years and over) and without the implementation of Augmented Reality technology Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5569 10.31315/telematika.v18i3.5569 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 375-383 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 375-383 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/5569/4264 10.31315/telematika.v18i3.5569.g4264 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6004 2022-07-15T01:51:43Z telematika:SE driver

Multiplatform-Based Digital Market Designs as Marketing and Sales Media of MSME Products in Pleret Village Kamal, Taufiq Ruscitasari, Zulfatun Hendriana, Yana Ravenna Rafail, Wahma digital market Multiplatform MSMEs Purpose : This study aims to design a multiplatform-based digital market to help rural MSMEs (Micro, Small, Medium Enterprises) market and sell their products in order to increase the competitiveness of MSMEs.Design/methodology/approach : The design of the digital platform of Ngedolke.com used a design thinking strategy. This study used the black box method to test the functional suitability of the developed application.Findings/result : This study produces an analysis and system design that is used to develop the digital platform of Ngedolke.com. Thus, it can be used to develop the system further.Originality/value/state of the art : The difference between this study and previous studies lies in the use of system design of a design thinking strategy. Besides, the technology used is multiplatform-based. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6004 10.31315/telematika.v18i3.6004 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 334-344 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 334-344 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6004/4268 10.31315/telematika.v18i3.6004.g4268 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6185 2022-07-15T01:51:44Z telematika:AI driver

Penerapan Jaringan Syaraf Tiruan pada Hidung Elektronik Cerdas untuk Deteksi Daging Babi A, MS Hendriyawan Aries, Baby Daging Babi Hidung Elektronik Jaringan Syaraf Tiruan MATLAB Tingkat komsumsi daging sapi di Indonesia terus naik dari tahun ke tahun terlihat dari permintaan pasar yang terus meningkat terutama pada perayaan hari besar dan hari raya. Akan tetapi peningkatan permintaan pasar akan daging sapi masih kerap dimanfaatkan oleh oknum tak bertanggung jawab yang mencampur daging sapi dengan daging babi. berdasarkan fakta tersebut maka dibuat sebuah sistem electronic nose yang dapat membedakan antara daging sapi murni dengan daging sapi bercampur babi berdasarkan karakteristik aroma. Alat ini menerapkan jaringan syaraf tiruan (JST) backpropagation yang dilatih menggunakan aplikasi MATLAB untuk mengenali pola dari aroma sampel daging yang ditangkap menggunakan rangkaian sensor gas TGS2602, TGS2620, TGS2610 dan TGS2611, kemudian mengklasifikasikannya dalam dua kelas yaitu MURNI dan CAMPURAN. Sampel daging segar yang digunakan untuk pengujian ada 4 macam yaitu daging sapi murni, daging campuran 25%, 50% dan 75% dengan total sampel sebanyak 30 terdiri dari 15 sampel murni dan 15 sampel campuran. Dari pengujian tersebut didapat nilai akurasi, presisi, sensitivity dan specificity sebesar 100% menggunakan confusion matrix. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6185 10.31315/telematika.v18i3.6185 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 282-296 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 282-296 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6185/4247 10.31315/telematika.v18i3.6185.g4247 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6300 2022-07-15T01:51:44Z telematika:SE driver

K-Means Algorithm and Binary Search on FiBuSI Khuzaifi, Ahmad Sari, Ratih Titi Komala FiBuSI Application Programming K-Means Binary Search Purpose: Create an application called FiBuSI (Find Business and Stock Investment) using the k-means algorithm and binary search for data search features. This application is intended for entrepreneurs and investors where they can interact with each other to build a joint business.Method: Using the RAD (Rapid Application Development) Method which focuses on system testing based on user experience related to Blackbox Testing using the Katalon Studio tools for testing functions on the FiBuSI application.Result: Based on the results of testing the FiBuSI application which focuses on the success of application functions and algorithm implementation, that each application function is successfully executed (PASSED) based on testing using the Katalon Studio tools. Meanwhile, testing the k-means algorithm (data filter) and binary search (search for letter data) was also successfully carried out by testing it directly by the user on the FiBuSI application and also using the results from the Katalon Studio tools.State of the art: Based on several studies that have been done previously related to the use of the k-means algorithm and binary search that this algorithm is carried out on 2 different features but in 1 application for business data search. In concept, the FiBuSI application focuses on bringing together entrepreneurs and investors in one platform. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6300 10.31315/telematika.v18i3.6300 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 361-374 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 361-374 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6300/4269 10.31315/telematika.v18i3.6300.g4269 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6415 2022-07-15T06:09:34Z telematika:GEN driver

STMIK PalComTech Customer Service Questionnaire Processing Application Design Triwahyuni, Atin Hartati, Eka Setiawan, Hera Triani, Riska Dashboard Customer Service Questionnaire Purpose: The focus of this research is to create a Consumer Service Questionnaire Dashboard application that can perform questionnaire data processing, service satisfaction analysis and reporting the results of service improvement recommendations at STMIK PalComTech.Design/methodology/approach: This study uses the Prototype method, where this method can interact with the user during user creation. This method consists of five stages, namely communication, planning quickly, modeling the design quickly, making prototypes, and submitting the system or software to the user or users to be tested using the black box testing method.Findings/result: The results of this study resulted in an application for processing customer service questionnaires from STMIK PalComTech, to simplify and shorten UPT-PM staff in preparing reports on the results of the questionnaire recap, reporting and distributing the results of the questionnaire recap of the Head of UPT-PM.Originality/value/state of the art: The system testing technique used in this study is black box testing, this testing technique focuses on the functional specifications of the software, this test is also used to find errors in the system, for example interface errors, performance errors, incorrect or missing functions. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6415 10.31315/telematika.v19i1.6415 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 47-58 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 47-58 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6415/4425 10.31315/telematika.v19i1.6415.g4425 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6447 2022-07-15T06:09:34Z telematika:GEN driver

The Development of Social Media Intelligence System for Citizen Opinion and Perception Analysis over Government Policy Habibi, Muhammad Ma'arif, Muhammad Rifqi Subekti, Dayat Sentiment Analysis Topic Modeling Machine Learning In Indonesia, community involvement in development planning and public policy has generally been carried out but limitedly. Social media uploads regarding public perceptions of policy implementation in the field are valuable input for those who quickly and accurately upload existing problems.The problems that arise from this effort to use social media are 1) how to detect public conversations related to a public policy. 2) Social media data collected extensively and accelerating can be processed quickly to get real-time analysis results. 3) Making the analysis results accessible in an interactive and representative form allows government policymakers to explore appropriate data and information to formulate and formulate public policies.This research produces a social media intelligence platform that can unite public opinion regarding public perceptions of the implementation of policies issued by the government, especially local governments in Indonesia. Based on modeling the topic of Covid-19 vaccination cases, 11 topics of discussion were obtained. While the sentiment analysis results of the 11 issues resulted, topic 6 had the most negative sentiment values regarding the development of Covid-19 vaccination in Indonesia. At the same time, topics with the most positive sentiment values are topic three and topic 10. These topics discuss the vaccination process carried out by health procedures (prokes) and government policies related to COVID-19 vaccination. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6447 10.31315/telematika.v19i1.6447 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 31-46 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 31-46 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6447/4418 10.31315/telematika.v19i1.6447.g4418 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6450 2022-07-15T06:09:34Z telematika:GEN driver

Identification Of Keywords That Impact Of Increasing The Click Through Rate Of Online Advertising On Search Engines Murdiyanto, Aris Wahyu Himawan, Arif keywords identification Click Through Rate search engines digital advertising Purpose: To identify keywords that can be chosen to increase CTR on the website so that the potential revenue of targeted prospects through search engines is higher.Design/methodology/approach: This study applies the weighted product method based on the criteria that will be determined to find the best keyword list.Findings/result: The results of identification by ranking using the weighted product method based on the criteria C1, C2, and C3 resulted in an average increase in CTR of 16.18% to 22.92%. With this increase, business owners can be more efficient in the online advertising process.Originality/value/state of the art: The identification of keywords that can be chosen to increase CTR on a website by ranking using the weighted product method has never been done by previous researchers.  Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6450 10.31315/telematika.v19i1.6450 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 77-90 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 77-90 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6450/4427 10.31315/telematika.v19i1.6450.g4427 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6460 2022-09-18T02:26:33Z telematika:AI driver

Classification of Damaged Road Images Using the Convolutional Neural Network Method Riyandi, Arif Widodo, Tony Uyun, Shofwatul Objective: Automatic identification is carried out with the help of a tool that can take an image of road conditions and automatically distinguish the types of road damage, the location of road damage in the image and calculate the level of road damage according to the type of road damage.Design/method/approach: Identification of damaged roads usually uses manual RCI system which requires high cost. In this study, a comparison framework is proposed to determine the performance of the image pre-processing model on the image classification algorithm.Results: Based on 733 image data classified using the CNN method from 4 models of pre-processing stages, it can be concluded that training from grayscale images produces the best level of accuracy with a training accuracy value of 88% and validation accuracy reaching 99%.Authenticity/state of the art: Testing of 4 pre-processing models against the classification algorithm used as a comparison resulted in the best algorithm/method for managing road images. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6460 10.31315/telematika.v19i2.6460 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 147-158 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 147-158 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6460/4668 10.31315/telematika.v19i2.6460.g4668 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6534 2022-09-18T02:26:33Z telematika:GEN driver

Framework Management to Minimize Risk in Protecting Enterprise Systems: Systematic Literature Review Adiyono, Soni Risaldi, Romy Aziz Widodo, Aris Puji Sediyono, Eko Enterprise System Management Enterprise System Security framework ERP System Information Security Purpose: This study aims to determine the efforts to minimize the occurrence of risks in enterprise systems and how far the framework is applied to an organization, as well as what steps must be applied in anticipation of it.Design/methodology/approach: This study uses a systematic review research method of literature published by international journals in the period 2016 to 2021 which is subscribed to by Diponegoro University.Findings/result: Most of the selected journals stated that in an effort to secure enterprise systems in an organization, they really consider several aspects in it, especially in terms of cost which is one of the biggest considerations in it, besides that support from policy makers must be needed to make guidelines in implementing framework (framework) regarding the limitations of Authentication access and interaction on a system.Originality/value/state of the art: the method applied will focus on discussing the realm of enterprise systems, specifically discussing framework management in an effort to minimize risks to enterprise systems.  Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6534 10.31315/telematika.v19i2.6534 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 159-172 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 159-172 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6534/4669 10.31315/telematika.v19i2.6534.g4669 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6577 2022-07-15T06:09:34Z telematika:GEN driver

Analisis Sentimen Vaksin Covid-19 Menggunakan Algoritma Naive Bayes dan Perbaikan Kata Levenshtein Distance Prasastio, Fahmi Reza Heriyanto, Heriyanto Kaswidjanti, Wilis sentiment analysis vaccine naive bayes levenshtein distance Tujuan: Mengetahui seberapa akurat penggunaan perbaikan kata metode Levenshtein Distance terhadap analisis sentimen vaksin Covid-19 menggunakan metode Naïve Bayes.Perancangan/metode/pendekatan: Menerapkan perbaikan kata Levenshtein Distance untuk preprocessing dan algoritma Naïve Bayes dalam melakukan analisis sentimen komentar masyarakat tentang vaksin Covid-19.Hasil: Dengan diterapkannya perbaikan kata pada dataset yang digunakan dapat meningkatkan akurasi dari model Naïve Bayes yang dibangun. Akurasi pengujian menggunakan data uji lama yang berjumlah 479 data meningkat dari 61% menjadi 71% dan pengujian dengan data uji baru yang berjumlah 100 data akurasi meningkat dari 59% menjadi 66%. Namun untuk klasifikasi data testing baru memperoleh akurasi yang cukup rendah walaupun data yang dites hanya berjumlah 100 data, hal ini disebabkan oleh sistem yang kurang mampu dalam melakukan klasifikasi data baru yang belum pernah dilakukan training sebelumnya.Keaslian/ state of the art: Penelitian ini menggunakan data dengan jumlah 2394 data yang berasal dari komentar akun Instagram Kemenkes RI. Untuk preprocessing dilakukan perbaikan kata dengan algoritma Levenshtein Distance dan untuk analisis komentar menggunakan algoritma Naïve Bayes dengan ekstraksi fitur TF-IDF. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6577 10.31315/telematika.v19i1.6577 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 91-104 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 91-104 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6577/4428 10.31315/telematika.v19i1.6577.g4428 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6650 2022-07-15T01:51:44Z telematika:GEN driver

Recurrent Neural Network With Gate Recurrent Unit For Stock Price Prediction Caniago, Afif Ilham Kaswidjanti, Wilis Juwairiah, Juwairiah stock exchange RNN GRU Shallow Stacked Tecnical analysis Chartist Stock price prediction is a solution to reduce the risk of loss from investing in stocks go public. Although stock prices can be analyzed by stock experts, this analysis is analytical bias. Recurrent Neural Network (RNN) is a machine learning algorithm that can predict a time series data, non-linear data and non-stationary. However, RNNs have a vanishing gradient problem when dealing with long memory dependencies. The Gate Recurrent Unit (GRU) has the ability to handle long memory dependency data. In this study, researchers will evaluate the parameters of the RNN-GRU architecture that affect predictions with MAE, RMSE, DA, and MAPE as benchmarks. The architectural parameters tested are the number of units/neurons, hidden layers (Shallow and Stacked) and input data (Chartist and TA). The best number of units/neurons is not the same in all predicted cases. The best architecture of RNN-GRU is Stacked. The best input data is TA. Stock price predictions with RNN-GRU have different performance depending on how far the model predicts and the company's liquidity. The error value in this study (MAE, RMSE, MAPE) constantly increases as the label range increases. In this study, there are six data on stock prices with different companies. Liquid companies have a lower error value than non-liquid companies. Jurusan Informatika 2021-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6650 10.31315/telematika.v18i3.6650 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 18 No. 3 (2021): Edisi Oktober 2021; 345-360 Telematika; Vol 18 No 3 (2021): Edisi Oktober 2021; 345-360 2460-9021 1829-667X 10.31315/telematika.v18i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6650/4250 10.31315/telematika.v18i3.6650.g4250 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/6878 2022-07-15T06:09:34Z telematika:GEN driver

Analysis of the AHP-WP Method in the Decision Support System for the Assessment of Outstanding Students at ITEKES Bali Kusuma Putra, Komang Gde Hendra Candiasa, I Made Indrawan, Gede decision support system student outstanding analitycal hierarchy proces weighted product Purpose: This study aims to analyze and determine the effectiveness of the combination of decision-making methods in the selection of outstanding students using the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods.Design/methodology/approach: A quantitative approach is used to analyze the combination of AHP and WP methods in determining outstanding students. The ranking results were analyzed using Mean Absolute Percentage Error (MAPE).Findings/result: This research produces a combination analysis of the AHP and WP decision-making methods, so that it can be used for implementation into information systems.Originality/value/state of the art: The difference between this study and previous studies is the combination of methods used in this study. An analysis of the effect of several variables in increasing accuracy is also produced. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6878 10.31315/telematika.v19i1.6878 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 59-76 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 59-76 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/6878/4426 10.31315/telematika.v19i1.6878.g4426 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7000 2022-09-18T02:26:33Z telematika:GEN driver

Knowledge Management In Instiki E-Learning To Increase Student Learning Satisfaction Kusuma, Aniek Suryanti Agustini, Ketut Sudatha, I Gde Wawan Warpala, I Wayan Sukra Knowledge Management Learning Management System E-Learning Hybrid Learning Purpose: The use of the concept of knowledge management can manage the knowledge of the teacher or lecturer and then it can be conveyed to the studentsDesign/methodology/approach: Knowledge Management SystemFindings/result: The application of the Knowledge Management System at the INSTIKI LMS was able to increase student learning satisfaction. The results of the questionnaire assessment show that student learning satisfaction increases after implementing INSTIKI e-learning, the average value of studentOriginality/value/state of the art: Implementation of Knowledge Management System on INSTIKI campus Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7000 10.31315/telematika.v19i2.7000 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 173-184 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 173-184 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7000/4670 10.31315/telematika.v19i2.7000.g4670 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7044 2022-09-18T02:26:33Z telematika:AI driver

Detection of Student Drowsiness Using Ensemble Regression Trees in Online Learning During a COVID-19 Pandemic Udayana, I Putu Agus Eka Darma Kherismawati, Ni Putu Eka Sudipa, I Gede Iwan Drowsiness Detection Online Leraning Ensemble Regression Tree COVID 19 Online lectures are mandatory to deal with the implementation of education during the COVID-19 pandemic. This significant change certainly creates a different experience for students. Regarding online learning, several public health experts and ophthalmologists say that residual radiation from electronic screens is causing an epidemic of eye fatigue. Research on smart classrooms actually appeared several years ago, but in reality it has not been implemented according to the planned concept. The current smart classroom research environment only uses outdated methods, which make the computer system incongruent (such as decision trees in video feeds) or only to the level of empirical studies or blueprints, which are not much help for other academic footing or reference materials. to students. This study aims to build an intelligent system that can evaluate students' attention during online classes, use teaching videos as learning feeds and input for predictions and also use advanced algorithms in several computational domains, namely face segmentation, landmarking, PERCLOS observations, Yawning and decision analysis using Ensemble Regression Trees to detect students' sleepiness, which is expected to patch up the shortcomings of the PERCLOS algorithm and the problems found in the single regression tree-based implementation. Based on the results of the tests that have been carried out, the system developed has been able to observe sleepy objects in learning videos with an accuracy of 80% so that later it can be a lesson for teachers why there are students who are sleepy during online classes either because of uninteresting material or other reasons. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7044 10.31315/telematika.v19i2.7044 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 229-244 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 229-244 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7044/4675 10.31315/telematika.v19i2.7044.g4675 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7059 2022-11-22T06:52:23Z telematika:GEN driver

Capability Level Analysis of IT Governance Using COBIT 5 on Continuity and Availability Of Services (Case Study: LMS Spada Wimaya) Putri, Dyah Anggraini Kartika Juwairiah, Juwairiah Kodong, Frans Richard Purpose: This study aims to assess the capability level to determine the condition of the capability level as-is, to-be, gap analysis and provide recommendations for improving IT governance in the continuity and availability process of LMS Spada Wimaya service. Design/methodology/approach: The capability level assessment refers to the COBIT 5 Process Assessment Model (PAM) assessment criteria with the research stages adopting the COBIT 5 Assessment Process Activities. Findings/result: Based on the urgency and problems that occur in LMS Spada Wimaya related to the continuity of service availability, the appropriate COBIT 5 enterprise goals are chosen, namely Business Service Continuity and Availability which describes in achieving the vision and mission goals of UPN "Veteran" Yogyakarta related to the procurement of LMS Spada Wimaya. The process of mapping results is prioritized based on impact and importance. The results of the assessment of the current capability level (as-is) in the BAI06, DSS03, DSS05, and MEA01 processes are at level 2 with the expected target capability level (to-be) at level 3 with a gap level of 1. DSS01, DSS02, and DSS04 are at level 1 with a target capability level (to-be) expected at level 3 with a gap level of 2. output criteria, setting performance goals and targets, making Standard Operating Procedures (SOP), conducting performance assessments to ensure compliance. Originality/value/state of the art: This study has the same focus as previous research, which is measuring the ability of the IT governance level with the criteria for the COBIT 5 Model Assessment Criteria (PAM), but is implemented in a different case study and the focus of the process is in accordance with the results of mapping the alignment of organizational goals with COBIT 5 IT goals according to urgency and problems that describe in achieving the vision and mission of the object of research. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7059 10.31315/telematika.v19i3.7059 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 283-294 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 283-294 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7059/4751 10.31315/telematika.v19i3.7059.g4751 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7165 2022-07-15T06:09:34Z telematika:GEN driver

Success Measurement of E-Learning Spada Wimaya at Universitas Pembangunan Nasional “Veteran” Yogyakarta Using Delone and Mclean Model Approach Aryanti, Dona Simanjuntak, Oliver Samuel Juwairiah, Juwairiah Delone and Mclean E-learning SPADA Wimaya Success Measurement SEM Purpose: This study aims to measure success and determine the factors that support or hinder the success of the e-learning SPADA Wimaya.Method: This study adapts the development of the DeLone and McLean Model 2003. The data used are primary data obtained from the answers of 387 users of the e-learning SPADA Wimaya Pembangunan Nasional “Veteran” Yogyakarta University as respondents in the distributed questionnaire. The results of the questionnaire were processed using SPSS to test descriptive of the data. After that, the data is processed using Structural Equation Modeling (SEM) for testing the inner model and outer model which includes hypothesis testing through SmartPLS software.Result: Of the nine proposed hypotheses, six were accepted and the other three were rejected. Because not all variables affect each other significantly, the e-learning SPADA Wimaya is declared to have not been successful. The factors that hinder the success of the e-learning SPADA Wimaya are the security indicator on the system quality variable, responsive indicator on the service quality variable and communication effectiveness on the net benefit variable. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7165 10.31315/telematika.v19i1.7165 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 105-116 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 105-116 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7165/4429 10.31315/telematika.v19i1.7165.g4429 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7174 2023-03-04T07:04:20Z telematika:GEN driver

COMPARISON OF MAUT METHOD WITH MABAC IN GIVING EMPLOYEES SALARY BONUS AT PT. ARTA JAYA ELECTRIC Putra, I Nyoman Tri Anindia Kartini, Ketut Sepdyana Putri, Ni Putu Hanny Wulandari SPK MABAC MAUT Tujuan: PT. Arta Jaya Elektrik memiliki karyawan yang setiap bulan diberikan gaji dan setiap 6 bulan diberikan bonus gaji. Dalam proses penentuan bonus karyawan masih menggunakan Microsoft Excel sehingga terkadang terjadi kesalahan dalam proses penginputan data yang akan digunakan untuk penilaian karyawan. Selain itu, dikarenakan harus membuat rekapan data penunjang pemberian bonus karyawan.Perancangan/metode/pendekatan: Perancangan sistem dibuat untuk dapat mengelola data karyawan, data kriteria, data sub-kriteria, data penilaian, data perhitungan, dan data hasil akhir. Pendekatan Metode MAUT dan MABAC digunakan karena ingin melakukan perbandingan untuk memilih metode yang paling tepat dan mudah dalam menentukan bonus gaji karyawan. Hasil: Pengujian perhitungan menggunakan MAUT dan MABAC menghasilkan urutan hasil peringkat yang sama. Namun hasil total perhitungan menunjukan jumlah yang berbeda. Keaslian/ state of the art: Berdasarkan penelitian terdahulu, dalam penelitian ini menggunakan kriteria absensi, keterlambatan, lembur, dan kinerja karyawan dalam melakukan perhitungan metode MAUT dan MABAC untuk mencari hasil akhir perangkingan alternatif. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7174 10.31315/telematika.v19i1.7174 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 133-146 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 133-146 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7174/4431 10.31315/telematika.v19i1.7174.g4431 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7181 2022-07-15T06:09:34Z telematika:GEN driver

Group Decision Support System Using SMART-COPELAND SCORE Model In Choosing The Best Alternative Pair Waas, Devi Valentino Arsitana, Made Dona Wahyu Permana, I Putu Hendika Wiratama, I Komang Sudipa, I Gede Iwan GDSS SMART Copeland Score Voting Aggregation Preferences Purpose: Adjust the Group Decision Support System (GDSS) model in completing case studies of selecting the best alternative candidate pairs for the OSIS core board with many decision-makers and problems in the differences in the preferences of decision-makers as well as modeling in decision making with multi-criteria and multi-attributes and combining preferences decision-makers to choose the best alternative partner candidate.Design/methodology/approach: The Group Decision Support System (GDSS) model combines the SMART method for modeling multi-criteria and multi-attribute assessments and the Copeland Score model for aggregating the judgments of five decision-makers against the selected pair of OSIS core board candidates using a voting mechanism.Findings/result: The comparison test for the manual calculation of the SMART- Copeland Score Model method with the results of the system calculation is the same. From the ten alternative data in the first stage of the test through the SMART method calculation, it then passes into four alternatives divided into two alternative candidate pairs, namely alternative candidate pairs (A1, A3) and alternative candidate pairs (A2, A4). The second stage test uses calculations Copeland Score voting, which produces the best alternative candidate pair, namely alternative (A1, A3) with a final point score = 4.Originality/value/state of the art: Based on a review of previous research, this study uses line-up criteria, written tests, and interview tests with the SMART method to calculate alternative scores on each criteria, and the Copeland Score model to aggregate decision makers' preferences to produce the best alternative candidate pairs. In calculating the final value of the alternative ranking. Jurusan Informatika 2022-02-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7181 10.31315/telematika.v19i1.7181 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 1 (2022): Edisi Februari 2022; 117-132 Telematika; Vol 19 No 1 (2022): Edisi Februari 2022; 117-132 2460-9021 1829-667X 10.31315/telematika.v19i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7181/4430 10.31315/telematika.v19i1.7181.g4430 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7246 2022-09-18T02:26:33Z telematika:AI driver

Mask Detection System Using Convolutional Neural Network Method on Surveillance Camera Asana, I Made Dwi Putra Pradana, Gede Aldhi Handika, I Putu Susila Murpratiwi, Santi Ika Covid-19 Convolutional Neural Network Deep Learning Mask Detection Computer Vision The Covid-19 has been an epidemic that has taken the world by storm since the beginning of 2020. This Covid-19 outbreak can spread easily through the air. Because Covid-19 can transmit easily, the government implements new behavior based on an adaption to develop a clean and healthy lifestyle which is often called the new normal. One way to live the new normal is to wear a mask when leaving the house. To help increase public awareness in using masks, numerous technology- based studies have been carried out. This article explain an application using the python programming language that applies digital image processing in terms of detecting the use of masks using Deep Learning with the Convolutional Neural Network (CNN) method to classify data that has been labeled using the supervised learning method. In designing this CNN architectural model, a total of 2110 images of people wearing and without wearing masks will be used, this dataset will be divided into 2 parts, with a rate of 8020, where 80 of the dataset will be used as training data, 20 is used as validation data. In testing the model by taking a total of 100 images with a 5050 ratio between face images using masks and not using masks tested using a confusion matrix, it produces 97% of an accuracy rate, 100% of precision rate, and 94% of recall in recognizing facial images that use masks and don't use masks  Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7246 10.31315/telematika.v19i2.7246 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 201-214 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 201-214 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7246/4673 10.31315/telematika.v19i2.7246.g4673 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7363 2022-09-18T02:26:34Z telematika:SE driver

Implementation Of Mobile-Based OOAD Interactive Learning Media Putra, I Nyoman Tri Anindia Kartini, Ketut Sepdyana Winatha, Komang Redy Interactive Leearning Media OOAD Mobile The lack of interest in student learning is due to the learning media used are less attractive and effective to understand the material. This study aims to implement mobile-based interactive learning media regarding OOAD material. The media feasibility test uses a blackbox testing scenario and the analysis uses the Gutman scale technique. From the test results, it was found that the percentage of blackbox testing was 100% and the functional requirements test by the resource persons obtained a percentage of 100%. Based on the results of these studies, it can be explained that this learning media is very good and has been feasible to be implemented. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7363 10.31315/telematika.v19i2.7363 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 271-282 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 271-282 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7363/4678 10.31315/telematika.v19i2.7363.g4678 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7418 2022-11-22T06:53:09Z telematika:GEN driver

Text Message Classification using Multiclass Support Vector Machine on Information Service Chatbot in the Informatics Department UPN “Veteran” Yogyakarta Putra, Rafly Pradana Pratomo, Awang Hendrianto Perwira, Rifki Indra chatbot nlp svm Tujuan: Menguji performa dari algoritma Multiclass Support Vector Machine dalam dalam tingkat akurasi, presisi, dan recall untuk melakukan klasifikasi pada pesan teks chatbot.Perancangan/metode/pendekatan: Menggunakan algoritma Multiclass Support Vector Machine untuk melakukan klasifikasi terhadap dataset yang bersifat nonbiner atau dataset yang memiliki lebih dari dua kelas.Hasil: Berdasarkan hasil penelitian dan pembahasan yang dilakukan, Algoritma Multiclass SVM dapat melakukan klasifikasi teks pesan yang dikirimkan dengan baik berdasarkan kategori pesan yang berkaitan dengan informasi yang ada di jurusan informasi, seperti administratif, dokumen, jadwal, kegiatan dan sapaan, dengan menunjukkan nilai akurasi sebesar 87%, nilai presisi sebesar 89% dan nilai recall sebesar 87%. Penelitian ini menggunakan dataset yang berjumlah sebanyak 950 data dengan pembagian data latih sebanyak 75% dari total keseluruhan data dan data uji sebanyak 25% dari total keseluruhan data.Keaslian/ state of the art: Penelitian ini memiliki perbedaan dalam hal jenis data yang digunakan adalah data teks pesan yang terbagi ke dalam 5 kategori, nilai parameter C dan gamma yang digunakan, dan hasil yang diperoleh jika dibandingkan dengan penelitian sebelumnya. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7418 10.31315/telematika.v19i3.7418 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 295-310 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 295-310 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7418/4752 10.31315/telematika.v19i3.7418.g4752 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7419 2022-09-18T02:26:34Z telematika:AI driver

Deep-RIC: Plastic Waste Classification using Deep Learning and Resin Identification Codes (RIC) Listyalina, Latifah Yudianingsih, Yudianingsih Soedjono, Adjie Wibowo Utari, Evrita Lusiana Dharmawan, Dhimas Arief deep learning image plastic waste classification Resin Identification Codes In this study, the authors designed an algorithm based on deep learning that can automatically classify plastic waste according to Resin Identification Codes (RIC). The proposed algorithm is built through several stages as follows. In the first stage, image acquisition of plastic waste is carried out, which is the input of the designed algorithm. The acquired plastic waste image must display the resin code of the plastic waste to be classified. Furthermore, the acquired image is divided into two sets, namely training and testing sets. The training set contains images of plastic waste used in the training phase of the deep learning architecture DenseNet-121 to identify the resin code of each plastic waste image and classify it into the appropriate class. The training phase is run for 100 epochs, and at each epoch, the cross-entropy loss function is calculated, which expresses the performance of the deep learning architectures in classifying plastic waste images. In the next stage, a trained deep learning architecture is used to classify the plastic waste images from the test set. Classification performance in the test set is also expressed as the cross-entropy loss function value. In addition, the accuracy value has also been calculated, which shows the percentage of the number of plastic waste images successfully classified correctly to the total number of plastic waste images in the test set, which the best accuracy is equal to 85%. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7419 10.31315/telematika.v19i2.7419 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 215-228 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 215-228 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7419/4674 10.31315/telematika.v19i2.7419.g4674 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7544 2022-09-18T02:26:34Z telematika:AI driver

Implementation Of The Double Exponential Smoothing Method In Determining The Planting Time In Strawberry Plantations Shabir, Fadly Abdullah, Ahmad Irfan Asrul, Billy Eden William Nur, Sitti Alifah Amilhusna Prediction Strawberry Double Exponential Smoothing MAPE Purpose: This research aims to provide recommendations for planting season based on predictions of rainfall, air temperature, and wind speed based on the website.Design/methodology/approach: This study implemented the Double exponential smoothing to predict rainfall, air temperature, and monthly wind speed one year in the future using past data.Findings/result: This study has succeeded in providing recommendations for planting season. Based on the results of the accuracy calculation between the prediction results and the actual data using the Mean Absolute Percetage Error (MAPE), each has a forecast error value of 30.69% for rainfall, 0.63% air temperature, and 5.89% wind speed. Originality/value/state of the art: Research related to the application of Double exponential smoothing to determine the planting period. Based on the results of the accuracy calculation between the prediction results and the actual data using Mean Absolute Percetage Error (MAPE), this has never been done in previous studies. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7544 10.31315/telematika.v19i2.7544 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 259-270 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 259-270 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7544/4677 10.31315/telematika.v19i2.7544.g4677 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7564 2022-11-22T06:53:37Z telematika:GEN driver

IMPROVEMENT OF HANDWRITING JAVASCRAFT IMAGE QUALITY AND SEGMENTATION WITH CLOSING MORPHOLOGY AND ADAPTIVE THRESHOLDING METHODS Riyandi, Arif 'Uyun, Shofwatul Tujuan: Perbaikan kualitas citra yang putus-putus atau terlalu tipis pada aksara jawa tulisan tangan menggunakan operasi morfologi dan mengumpulkan dataset secara otomatis dari proses cropping dengan metode Connected Component Labeling.Perancangan/metode/pendekatan: Menerapkan metode operasi morfologi dalam perbaikan citra putus-putus dan metode connected component labeling untuk membantu cropping dalam mengumpulkan dataset secara otomatis.Hasil: Hasil uji coba dengan beberapa kernel yang berbeda antara operasi morfologi opening dan operasi morfologi closing terpilih operasi morfologi closing dengan kernel (45,45) pada bagian dilasi dan kernel (37,37) pada bagian erosi. Hasil dari segmentasi yang terpilih lanjut ke cropping dengan bantuan metode connected component labeling dan klasifikasi convolutional neural network yang diterapkan untuk mengklasifikasi citra aksara jawa dengan baik. Akurasi yang diperoleh adalah sebesar 94,27 % pada proses klasifikasi menggunakan data training dan akurasi 84,53% pada proses klasifikasi menggunakan data validasi.Keaslian/ state of the art: Pengujian dari operasi morfologi opening dan operasi morfologi closing dengan masing-masing 6 kernel berbeda pada proses segmentasi citra aksara jawa untuk perbaikan kualitas citra. Pengumpulan dataset secara otomatis dari hasil cropping citra dengan bantuan metode connected component labeling dan hasil dataset yang terkumpul diklasifikasi untuk masing-masing citra aksara jawa. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7564 10.31315/telematika.v19i3.7564 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 311-322 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 311-322 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7564/4753 10.31315/telematika.v19i3.7564.g4753 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7598 2022-09-18T02:26:34Z telematika:GEN driver

Feasibility Analysis of Information Technology Investment Using Cost Benefit Analysis Method Agusdin, Riza Prapascatama Aidil, Naufal Nur Cost Benefit Analysis IT Investment IT Feasibility Analysis Objective: One of the strategies that companies can do to survive amid fierce business competition is to invest in IT. Currently all companies need to invest in IT to improve company performance better but usually the budget costs that must be incurred by companies to make IT investments are very large. Therefore, it is necessary to analyze the feasibility of IT investment. This study aims to determine how much the costs incurred and the benefits obtained after creating a Social Media Analysis information system and also to find out whether the Social Media Analysis information system development project is feasible or not.Methods: This study uses the Cost Benefit Analysis method where the method compares the components of costs and benefits which are then recommended for a policy on investment projects. The Cost Benefit Analysis method is supported by several calculation criteria such as Net Present Value (NPV), Payback Period (PP), Return On Investment (ROI), and Benefit Cost Ratio (BCR).Results: The results showed that the NPV for 5 years was Rp. 300,138,606, PP was 2 years and 11 months, ROI was 9.03%, and BCR was 1.08. From the results of this study, it can be concluded that the Social Media Analysis information system investment project is feasible to continue. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7598 10.31315/telematika.v19i2.7598 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 245-258 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 245-258 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7598/4676 10.31315/telematika.v19i2.7598.g4676 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7601 2022-09-18T02:26:34Z telematika:GEN driver

Analysis of Sentiments and Emotions about Sinovac Vaccine Using Naive Bayes Akbar, Bagus Muhammad Akbar, Ahmad Taufiq Husaini, Rochmat analisis sentimen naïve bayes vaksin Tujuan:Banyak negara di dunia telah berusaha mengendalikan dampak pandemi COVID-19 melalui penggunaan vaksin. vaksin sinovac merupakan salah satu vaksin populer yang telah digunakan di beberapa negara termasuk Indonesia. Sejak hadirnya vaksin sinovac, persepsi masyarakat baik di lapangan maupun di media sosial semakin muncul antara setuju dan tidak setuju dengan vaksin tersebut. Persepsi masyarakat dunia di media sosial dapat dianalisis untuk mengetahui kategori sentimen dan tingkat emosional masyarakat terhadap penerimaan vaksin Sinovac.Perancangan/metode/pendekatan:Analisis dapat dilakukan melalui data mining yang menggunakan algoritma Naive Bayes untuk menghitung probabilitas dan statistik sehingga setiap opini dapat diklasifikasikan dalam kategori sentimen positif, negatif, atau netral. Dalam penelitian ini, sumber analisis data adalah persepsi publik yang mengandung kata kunci “sinovac” dari twitter. Pengujian menggunakan sentimen, sentimen, dan library syuzhet menunjukkan bahwa sentimen positif lebih tinggi daripada negatif dan netral. Sentimen negatif paling dipengaruhi oleh tingkat emosional kesedihan dan kemarahan. Sedangkan sentimen positif sangat dipengaruhi oleh kategori senang dan emosi campur aduk. Kategori emosi campuran lebih sesuai dengan sentimen positif.Hasil:Klasifikasi emosi terhadap data tweet dalam penelitian ini menunjukkan bahwa kategori emosi kegembiraan, dan campuran memiliki persentase tertinggi yang mengandung polaritas sentimen positif. Berdasarkan penelitian ini, kata kunci sinovac cenderung memunculkan sentimen positif. Polaritas mempengaruhi emosi, namun tidak sebaliknya. Karena terlihat bahwa nilai akurasi pada klasifikasi polaritas (dengan kedua library) telah meningkat ketika fitur emosi tidak diikutkan. Sedangkan nilai akurasi pada klasifikasi emosi justru meningkat ketika fitur polaritas diikutkan.Keaslian/ state of the art:Metode Naive Bayes (library setiment) dan metode Valence Shifter (library sentimentr) yang digunakan dalam analisis sentimen pada penelitian ini menunjukkan bahwa sentimen positif lebih tinggi daripada netral dan negatif. Hasil persentase sentimen positif oleh metode Valence Shifter lebih rendah daripada metode Naive Bayes. Pada metode Valence Shifter cenderung menghasilkan agregat yang lebih kecil antara hasil persentase sentimen positif dibanding netral dan negatif. Jurusan Informatika 2022-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7601 10.31315/telematika.v19i2.7601 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 2 (2022): Edisi Juni 2022; 185-200 Telematika; Vol 19 No 2 (2022): Edisi Juni 2022; 185-200 2460-9021 1829-667X 10.31315/telematika.v19i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7601/4672 10.31315/telematika.v19i2.7601.g4672 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7643 2024-12-02T00:49:15Z telematika:GEN driver

Monitoring Development Board based on InfluxDB and Grafana Noprianto, Noprianto Wijayaningrum, Vivi Nur Wakhidah, Rokhimatul Monitoring Development Board InfluxDB Grafana Purpose: Designing a sensor data monitoring system using a time series database and monitoring platform on a Development Board device.Design/methodology/approach: It begins with a requirement analysis, such as the preparation of the required software and hardware, followed by the creation of the system architecture that will be adopted. Then the development process from a predetermined design to the testing process to ensure the dashboard page can display data according to a predetermined scenario.Findings/result: From the research that has been done, produces a design of sensor data that is sent using the MQTT protocol via Node-RED, then stored in a time series database (InfluxDB) and displayed on the Grafana dashboard display.Originality/value/state of the art: Sensor data monitoring dashboard on Development Board devices Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7643 10.31315/telematika.v20i1.7643 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 81-90 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 81-90 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7643/5395 10.31315/telematika.v20i1.7643.g5395 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7697 2022-11-22T06:54:48Z telematika:GEN driver

Conv-Tire: Tire Condition Assessment using Convolutional Neural Networks Listyalina, Latifah Buyung, Irawadi Munir, Agus Qomaruddin Mustiadi, Ikhwan Dharmawan, Dhimas Arief convolutional neural network image tire tire quality Purpose: In this study, the authors designed an algorithm based on convolutional neural networks that can automatically assess tire quality.Design/methodology/approach: The proposed algorithm is built through several stages as follows. In the first stage, the tire images, which are the input of the designed algorithm, are acquired. Further, the acquired images are divided into two sets, namely training and testing sets. The training set contains tire images used in the training phase of several convolutional neural networks (CNN) architectures such as ResNet-50, MobileNetV2, Inception V3, and DenseNet-121. The training phase is carried out in a number of epochs, and at each epoch, the cross entropy loss function will be calculated which expresses the performance of the CNN architecture in classifying tire images. For this reason, the training stage requires a label or reference that shows the feasibility of the tires displayed in each image.Findings/result: In the testing phase, trained CNN architectures are used to classify tire images from the test set. Classification performance in the test set is also expressed in terms of cross-entropy loss function value. In addition, the accuracy value has also been calculated which shows the percentage of the number of tire images that are successfully classified correctly to the total number of tire images in the test set, namely the DenseNet-121 model has the best accuracy of 92.62%.Originality/value/state of the art: Given the high accuracy achieved by our algorithm, this work can be used as a reference by other researchers, specifically to benchmark their tire quality classification methods developed in the future. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7697 10.31315/telematika.v19i3.7697 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 323-336 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 323-336 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7697/4755 10.31315/telematika.v19i3.7697.g4755 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7709 2023-06-22T03:14:02Z telematika:GEN driver

Analisys Mortality Rate of Tuberculosis Patients Seen From Age and Length of Treatment at RSUD Dr. M. Haulussy Ambon Using the K-Means Clustering Algorithm for the Rapidminer Application Upuy, Doms Palembang, Citra Fathia Tuberculosis Clustering K-Means Tuberculosis (TB) is an infectious disease that causes major health problems in the world by the bacterium Mycobacterium tuberculosis. It spreads through the air when people with TB cough or sneeze. Maluku was in the 10th position with the most TB cases in Indonesia in 2016. Various programs and activities to control TB in Ambon City are carried out, from the process of finding cases, treating patients, health promotions to sputum examination. After that, an evaluation is carried out as an effort to prevent and control to measure the level of success and effectiveness of institutional programs in order to achieve organizational goals. To find out the development of TB cases in Maluku, especially the city of Ambon, the research conducted this time also used the k-means clustering algorithm for the rapidminer application to analyze the death rate of TB patients in terms of age and length of treatment at RSU Dr. M. Haulussy Ambon. The research conducted obtained that the highest number of patients who died were in cluster 1 with an age range of 36-55 years, then followed by the second position in cluster 0 with an age range of 6-33 years, and the last in cluster 2 with a total number of patients. died in the age range of 59-84 years. The length of stay of patients in the hospital varies from half a day to day 21 and is experienced by patients who recover as well as die. The highest patient mortality rate is in the productive age group, rarely does exercise and often engages in active activities and meets many people every day, smoking habits and lack of knowledge about health are the causes of more productive age groups suffering from TB Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7709 10.31315/telematika.v19i3.7709 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 337-346 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 337-346 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7709/4754 10.31315/telematika.v19i3.7709.g4754 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7734 2022-11-22T06:55:55Z telematika:GEN driver

Customer Loyalty Analysis On Online Travel Agent (OTA) Using American Customer Satisfaction Index (ACSI) And Structural Equation Modelling (SEM) Saputra, Yanu Ramdhani Jayadianti, Herlina Irawati, Dyah Ayu customer loyalty SEM ACSI Online Travel Agent Purpose: Knowing what affects customer loyalty in Online Travel Agent (OTA) Services. Which will help OTA Services to understand about customer satisfaction and customer loyalty so that they can develop their business in the future in order to get greater customer satisfaction and loyalty.Design/methodology/approach: Using the American Customer Satisfaction Index (ACSI) Model which explains the antecedents and consequences of customer satisfaction. In Antecedent there are variables of User Expectations, Perceived Quality, and Value benefits that have an impact on customer satisfaction variables then from causing customer complaints and customer loyalty. So that 9 research hypotheses are obtained based on the model used and tested using Structural Equation Modeling (SEM). Research requires data on respondents' answers distributed through digital media with a total need for 385 respondent data.Findings/result: After testing using SEM.The 9 hypotheses proposed show that 2 hypotheses are rejected and 7 hypotheses are accepted.Originality/value/state of the art: Previous research has been done but with different models and different methods. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7734 10.31315/telematika.v19i3.7734 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 347-358 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 347-358 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7734/4756 10.31315/telematika.v19i3.7734.g4756 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7757 2024-12-02T00:49:16Z telematika:GEN driver

Implementation of Penetration testing on Websites to Improve Security of Information Assets UPN "Veteran" Yogyakarta Sofyan, Herry Sugiarto, Meilan Akbar, Bagus Muhammad webserver pentest owasp framework. Purpose: This study aims to implement penetration testing on the website https://fit.upnyk.ac.id owned by Telematics UPN "Veteran" Yogyakarta to determine whether there are vulnerabilities or security holes in the web server. Then make an analysis based on the results of penetration testing on the web server using penetration testing tools (penetration testing scanner) so that recommendations for improvements are obtained to close security holes that can be used as a way for hackers to enter the system, as well as provide risk mitigation recommendations.Design/methodology/approach: This study uses the penetration test method which consists of five stages, namely literature study, information gathering, identification of system vulnerabilities, penetration testing and analysis. Penetration tests were carried out using acunetix tools and analysis using the OWASP and ISAAF methods.Findings/result: Based on research conducted on the website https://fit.upnyk.ac.id/ using the OWASP method, several vulnerabilities were found, including one vulnerability with a high level (high), three with a medium level and six with a low level (low), so that it can be it can be concluded that in general the level of vulnerability of the website is at the medium levelOriginality/value/state of the art: Penetration testing on the website can be done by identifying system vulnerabilities, penetration testing and analysis. The OWASP method can be used to find vulnerabilities on a website Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7757 10.31315/telematika.v20i2.7757 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 153-162 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 153-162 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7757/5654 10.31315/telematika.v20i2.7757.g5654 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7868 2024-12-02T00:49:15Z telematika:GEN driver

Autoregressive Integrated Moving Average (ARIMA) Models For Forecasting Sales Of Jeans Products Permata, Jenny Meilila Azani Cahya Habibi, Muhammad Sales Forecasting Autoregressive Integrated Moving Average Jeans Purpose: To be able to compete with other companies, it is necessary to estimate and forecast jeans products that will be ordered according to consumer demand every month, so that there is no excess inventory and product shortage. If there is a shortage of goods, the consumer will be disappointed with the seller, and vice versa if the goods are overstocked, the quality will continue to decline to the detriment of the seller and the buyer, resulting in a shortage of materials.Methodology: To overcome the problem of selling jeans products, the ARIMA method is suitable to overcome the problem of forecasting the stock of jeans sales. ARIMA model is a model that completely ignores the independent variables in making forecasts. ARIMA uses past and present values of the dependent variable to produce accurate short-term forecasting.Results: The built forecasting has a MAPE accuracy rate of 17.05% so it can be said that predicting has good results according to the criteria. Forecasting results in the following year show that sales tend to increase from the previous year.Originality: This research was conducted using sales data of jeans products at company XYZ and using the ARIMA method which previous researchers have never done. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7868 10.31315/telematika.v20i1.7868 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 31-40 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 31-40 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7868/5398 10.31315/telematika.v20i1.7868.g5398 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7929 2022-11-22T06:56:10Z telematika:GEN driver

Augmented Reality Introduction to Animals of the Archipelago to Grow the Nation's Love for Children Abadi, Anis Susila Dewi, Pipit Febriana Robi'in, Bambang Augmented reality Satwa nusantara Anak-anak Multimedia Purpose: Produce Augmented Reality applications as a medium for introducing Indonesian animals to foster the nation's love for children.Design/methodology/approach: AR applications are built using markers. AR application development uses the MDLC method, which consists of six stages, namely concept, design, material collection, manufacture, testing, and distribution.Findings/result: This research resulted in the application of Augmented Reality Animal Recognition. The results of the tests that have been carried out using the similarity test of 92% for testing the similarity of 3D objects on animals. SEQ testing with an average result of 91.18 on a scale of 10, so it can be concluded that the application has met the needs of users.Originality/value/state of the art: The development of this application focuses on AR applications with models of Indonesian animals and explanations of the characteristics of these animals. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7929 10.31315/telematika.v19i3.7929 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 359-370 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 359-370 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7929/4757 10.31315/telematika.v19i3.7929.g4757 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7949 2022-11-22T06:59:13Z telematika:GEN driver

Implementation of ERP in AKIP Evaluation System: A Case Study at The Ministry of Maritime Affairs And Fisheries Wiryadinata, Doni Sediyono, Eko Widodo, Aris Puji Evaluasi kinerja pada instansi pemerintah merupakan aktivitas analisis yang sistematis, pemberian nilai, atribut, dan pengenalan permasalahan, serta mempersembahkan solusi atas masalah yang ditemukan guna meningkatkan akuntabilitas dan peningkatan kinerja instansi pemerintah. Untuk pemerintahan di Indonesia, penilaian atas akuntabilitas kinerja merupakan sebuah cerminan organisasi dalam merepresentasikan kinerjanya, sehingga tidak mengherankan jika setiap instansi pemerintah berupaya semaksimal mungkin untuk meningkatkan kinerjanya sesuai dengan kriteria yang ditetapkan oleh tim evaluator. Baru-baru ini, MENPAN RB merevisi evaluasi AKIP ke dalam Peraturan MENPAN RB Nomor 88 Tahun 2021 dengan banyak perubahan yang cukup fundamental. Hal ini berdampak pada perubahan strategi organisasi untuk mengembangkan evaluasi evaluasi guna dapat memprediksi nilai akuntabilitas kinerja dengan bantuan teknologi informasi berbasis ERP, seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022. seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022. seperti contoh kasus yang terjadi pada Kementerian Kelautan dan Perikanan. Penelitian ini merupakan studi kasus bertujuan untuk mengetahui bagaimana penerapan ERP pada pelaksanaan evaluasi AKIP yang dijalankan oleh Inspektorat Jenderal Kementerian Kelautan dan Perikanan mulai dari dukungan infrastruktur dan jaringan teknologi informasi yang digunakan, tahap perancangan dan pengembangan perangkat lunak, serta implementasinya dapat digunakan pada pelaksanaannya AKIP pada Tahun 2022. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7949 10.31315/telematika.v19i3.7949 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 371-384 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 371-384 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7949/4758 10.31315/telematika.v19i3.7949.g4758 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7962 2022-11-22T06:59:15Z telematika:GEN driver

Implementation of Design Thinking for Web Based E-Voting Student Organization in Nahdlatul Ulama University of Yogyakarta Dewi, Pipit Febriana Badruzzaman, Abdulloh Misbahuddin, Muhammad Hanif Febriawan, Moh Rifqi Purpose: implement design thinking for web based E-Voting Student Organization in Nahdlatul Ulama University of YogyakartaDesign/methodology/approach:the method which used in this research is design thinking. The steps in this method are emphatize, define, ideate, prototype, and testFindings/result:the development of E-Voting is succesfully made according to user needsOriginality/value/state of the art:E-Voting web-based for student organization in Nahdlatul Ulama University of Yogyakarta Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7962 10.31315/telematika.v19i3.7962 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 385-396 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 385-396 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7962/4759 10.31315/telematika.v19i3.7962.g4759 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7979 2022-11-22T06:59:18Z telematika:GEN driver

Serious Game Design Of Sound Identification For Deaf Children Using The User Centered Design Rina, Fadmi Abadi, Anis Susila Huda, Sholeh Deaf Children Serious Game Sound identification User Centered Design The loss of hearing function in deaf children causes deaf children to experience obstacles in listening to the sound of objects or sounds of language as children generally hear. Therefore, it is necessary to optimize the hearing function of deaf children. The Development of Sound and Rhythm Perception Communication (PKPBI) is a special program to practice understanding sound so that the remaining hearing of deaf children can be maximized. So far, the PKPBI learning media at the sound identification stage used by the Karnna Manohara Yogyakarta Special School teacher is the keyboard. However, the keyboard has weaknesses such as the collection of sounds on the keyboard is very limited. Another problem is the Covid 19 pandemic, PKPBI learning is less than optimal due to limited face-to-face meetings. The purpose of this research is to design a serious game as a learning medium for sound identification for deaf children that can be used in the classroom and at home. The method used to design serious sound identification games is User Centered Design (UCD). Based on the research results, the design of this serious game can be developed into a serious game application to practice sound identification in deaf children. Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7979 10.31315/telematika.v19i3.7979 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 397-408 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 397-408 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7979/4760 10.31315/telematika.v19i3.7979.g4760 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/7988 2022-11-22T06:59:21Z telematika:GEN driver

Analysis of the usability quality of vocational high school websites using a user satisfaction approach Husaini, Rochmat Akbar, Bagus Muhammad Akbar, Ahmad Taufiq usability SEM user satisfaction Purpose: knowing the extent to which aspects that affect the level of user/visitor satisfaction in using the website.methodology: the method used is usability approach to measure website visitor satisfaction using Structural Equation Model (SEM) theory and SmartPLS v.3.2.9 software.Findings/result: found several variables that influence user satisfaction, and found variables that had no effect, even having a negative dependency value. In addition, it also produces priority recommendations for website improvement to meet user satisfaction.Originality: this study uses the palmer model usability approach [13] and the structural equation model. Which is different from previous research using the webqual method and Importance Performance Analisys [3] Jurusan Informatika 2022-10-31 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7988 10.31315/telematika.v19i3.7988 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 19 No. 3 (2022): Edisi Oktober 2022; 409-418 Telematika; Vol 19 No 3 (2022): Edisi Oktober 2022; 409-418 2460-9021 1829-667X 10.31315/telematika.v19i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/7988/4761 10.31315/telematika.v19i3.7988.g4761 Copyright (c) 2022 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8104 2024-12-02T00:49:17Z telematika:GEN driver

Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices Prapcoyo, Hari As'ad, Mohamad Sujito, Sujito Setyowibowo, Sigit Farida, Eni prediksi harga minyak mentah model pemulusan eksponensial ganda ETS Purpose: This study aims to predict the price of monthly crude oil quickly and accurately by using an easy model and with easily available software.Design/methodology/approach: This study compares the DES-Holts and ETS models to predict price of monthly crude oil.Findings/result: The results of this study recommend the ETS(M,N,N) model to predict the price of monthly crude oil which produces an accuracy value of RMSE and MAPE of 4.385812 and 6.499007 %, respectively.Originality/value/state of the art: This study implements the DES_Holt's and ETS models to predict price of monthly crude oil with an RMSE and MAPE forecasting accuracy that has never been done in previous studies.  Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8104 10.31315/telematika.v20i2.8104 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 202-214 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 202-214 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8104/5664 10.31315/telematika.v20i2.8104.g5664 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8482 2024-12-02T00:49:16Z telematika:GEN driver

Analysis Of Factors Affecting Interest Kai Access Application Users Using Models Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2) Firmansyah, Rifki Fauziah, Yuli Perwira, Rifki Indra Purpose: This study aims to analyze the factors that influence user interest in the KAI Access application using the Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2) model.Methodology: This study used the Structural Equation Modeling (SEM) method with two tests, namely the outer model and the inner model with the help of the SmartPLS Version 3 software. A total of 406 respondent data were used from the Special Region of Yogyakarta and also users of the KAI Access application.Results:  The results of the study show that of the fourteen hypotheses proposed in the study, only seven were accepted, namely social influence, facilitating conditions, hedonic motivation, price value, and habit. The strongest factors that have a significant effect are hedonic motivation and habit.State of the art: based on previous research, this study has quite similar characteristics but different cases, variables, and research samples. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8482 10.31315/telematika.v20i2.8482 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 174-186 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 174-186 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8482/5656 10.31315/telematika.v20i2.8482.g5656 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8774 2024-12-02T00:49:16Z telematika:GEN driver

Convolutional Neural Network for Identifying Tree Species Using Stem Images Pramesti, Nadia Rianto, Rianto accuracy CNN Epoch Identification Purpose: Identification of tree species based on stem images using programming assistance to design an automation tool to be able to distinguish tree species directly based on stem images from the new data entered.Design/methodology/approach: Identifying tree species is usually done using leaf images, in previous studies related to identifying tree species based on leaf images this resulted in quite high accuracy but was felt to be not optimal. In this study, we used a convolutional neural network to compare the accuracy of bar images.Findings/result: from 1000 tree trunk image data, identification was carried out using the help of python with the CNN method it can be concluded that the test results used the best acuration at epoch 25 with a value reaching 96.80%Originality/value/state of the art: Research with theme identification of tree species based on stem images using the CNN method has never been done by previous researchers.  Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8774 10.31315/telematika.v20i2.8774 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 163-173 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 163-173 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8774/5655 10.31315/telematika.v20i2.8774.g5655 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8827 2024-12-02T00:49:17Z telematika:GEN driver

Sentiment Analysis Of Student Opinion Related To Online Learning Using Naïve Bayes Classifier Algorithm And SVM With Adaboost On Twitter Social Media Ramli, Mohammad Rizal Sulastri, Heni Rianto, Rianto adaboost sentiment analysis covid-19 online lecture naïve bayes svm twitter Twitter is one of the social media that functions to express opinions on issues or problems that are currently happening, such as problems in the social, economic, educational and other fields. One of the issues being discussed so far is online learning. The government has issued a policy, one of which is for all students to study at home online by using a network to be able to interact with each other like in the classroom. The government's reason for issuing this policy is to break the chain of the spread of the Covid-19 virus, which until now has not subsided. Regarding this online learning policy, there are pros and cons. This opinion is widely expressed on social media, one of which is Twitter. Sentiment analysis is a method for analyzing an opinion which aims to classify texts. The Naïve Bayes Classifier and Support Vector Machine methods are methods machine learning that can be used for sentiment analysis. The problem in classifying text is that the resulting accuracy is less than optimal, so feature selection or boosting is needed to improve its accuracy. In this study, optimization of boosting was carried out using Adaboost. The purpose of this study is to compare the performance of the algorithm before and after using Adaboost. The results of the sentiment analysis on online learning obtained the highest accuracy results by the Naïve Bayes Classifier algorithm coupled with Adaboost of 99.26%, with a precision of 99.39% and recall of 99.20%. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8827 10.31315/telematika.v20i2.8827 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 187-201 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 187-201 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8827/5659 10.31315/telematika.v20i2.8827.g5659 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8846 2025-12-09T08:39:05Z telematika:GEN driver

Quality Analysis of the Ahmad Dahlan University Digital Library Using the WebQual 4.0 and Importance Analysis Performance (IPA) Method. Tarmuji, Ali Akbardillah, K Moch Reza Dwi Digilib WebQual IPA Hipotesis UI/UX Purpose: This paper is the result of research which aims to obtain results of measuring the quality of web services from the Library Unit at Ahmad Dahlan University, especially from the perceptions of student users in order to prepare recommendations for improving services. This paper is the result of research which aims to obtain results of measuring the quality of web services, especially from perceptions student users in order to prepare recommendations for improving service mediaDesign/methodology/approach: Based on sampling data collected using a questionnaire and calculated using statistics. The next step is to measure the WebQuel 4.0 method, the results of which are combined with the Importance Performance Analysis (IPA) method to determine recommendations.Findings/result: The research results show that each independent variable, namely the usability variable and the information quality variable, partially has a relationship or is correlated with the dependent variable, namely user satisfaction, while the interaction service quality variable partially has no relationship or is uncorrelated with the dependent variable. The results of simultaneous hypothesis testing show that the independent variable has an effect on the dependent variable so that the hypothesis can be simultaneously accepted. Based on the analysis using the IPA method, there are three things in Quadrant 1 (Top Priority) which are not in accordance with user expectations and need to be improved, namely "the DIGILIB UAD web is easy to learn", "the DIGILIB UAD web has an attractive appearance", "the DIGILIB UAD web has the function of library web type”.Originality/value/state of the art: Based on previous research and the results of previous digilib web development, the research produced a new assessment of the quality measures of web services at UPT Libraries, and made it the main alternative for developing service media in a better direction. Jurusan Informatika 2023-11-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8846 10.31315/telematika.v20i3.8846 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 3 (2023): Edisi Oktober 2023; 373-391 Telematika; Vol 20 No 3 (2023): Edisi Oktober 2023; 373-391 2460-9021 1829-667X 10.31315/telematika.v20i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8846/6210 10.31315/telematika.v20i3.8846.g6210 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8868 2024-12-02T00:49:16Z telematika:GEN driver

Application Random Forest Method for Sentiment Analysis in Jamsostek Mobile Review Azmi, Tasya Auliya Ulul Hakim, Luthfi Novitasari, Dian Candra Rini Utami, Wika Dianita Utami Dianita JMO analisis sentimen machine learning Purpose: This study aims to monitor the service quality of JMO applications from time to time by classifying JMO user reviews into the class of positive, neutral, and negative sentiments.Design/methodology/approach : The method used in this study is the random forest classification method. Data processing in this study uses feature extraction, TF-IDF and labeling with the lexicon-based method.Findings/result: Based on the research results, it was found that the highest frequency of classification was the positive class with 17571 reviews compared to the neutral class with 8701 reviews and the negative class with 3876 reviews with an accuracy evaluation value of 93%, precision 88%, recall 93%, and f1-score 90%.Originality/value/state of the art:This study uses 150737 reviews that have been pre-processed using the random forest method and TF-IDF and lexicon-based feature extraction. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8868 10.31315/telematika.v20i1.8868 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 117-128 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 117-128 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8868/5404 10.31315/telematika.v20i1.8868.g5404 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8925 2024-12-02T00:49:15Z telematika:GEN driver

Digital Image Processing to Detect Cracks in Buildings Using Naïve Bayes Algorithm (Case Study: Faculty of Engineering, Halu Oleo University) Hassanah, Waode Siti Nurul Lestari, Yunda Puji Saputra, Rizal Adi Retakan Deteksi Retakan HSV YCbCr Metode Thresholding Algoritma Naïve Bayes Purpose: To detect cracks in the walls of buildings using digital image processing and the Naïve Bayes Algorithm.Design/methodology/approach: Using the YCbCr color model for the segmentation process and the HSV color model for the feature extraction process. This study also uses the Naïve Bayes Algorithm to calculate the probability of feature similarity between testing data and training data.Findings/result: Detecting cracks is an important task to check the condition of the structure. Manual testing is a recognized method of crack detection. In manual testing, crack sketches are prepared by hand and deviation states are recorded. Because the manual approach relies heavily on the knowledge and experience of experts, it lacks objectivity in quantitative analysis. In addition, the manual method takes quite a lot of time. Instead of the manual method, this research proposes digital-based crack detection by utilizing image processing. This study uses an intelligent model based on image processing techniques that have been processed in the HSV color space. In addition, this study also uses the YcbCr color space for feature extraction and classification using the Naïve Bayes Algorithm for crack detection analysis on building walls. The accuracy of the research test data reached 88.888888888888890%, while the training data achieved an accuracy of 93.333333333333330%.Originality/value/state of the art: This study has the same focus as previous research, namely detecting cracks in building walls, but has different methods and is implemented in case studies. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8925 10.31315/telematika.v20i1.8925 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 1-14 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 1-14 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8925/5396 10.31315/telematika.v20i1.8925.g5396 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8933 2024-12-02T00:49:16Z telematika:GEN driver

Design Automatic Parking Application of Amikom Purwokerto University Kisma, Atmaja Jalu Narendra Marcos, Hendra Application Parking Vehicle  Purpose: This study aims to deal with parking problems in the area of Amikom University, Purwokerto. In addition, this research is designed to implement theoretical and practical knowledge that has been obtained in lectures.Design/methodology/approach: In research on parking design applications in the Amikom University area, Purwokerto, library study methods and literature study methods are used. The amount of data can add insight and can make it easier to process data in research.Findings/result: This application will be able to help more Amikom Purwokerto University residents, especially in the Faculty of Computer Science. The use of this application will help find parking areas in FIK areas such as Basement Parking, Front Parking and Field Parking. In addition, security will be helped by this application because if it is implemented, vehicles parked in the reserved area will be tidier and safer. In addition, security does not need to find an empty parking area for users.Originality/value/state of the art: This research focuses on parking system design like previous studies. However, this research focuses more on designing parking applications at Amikom Purwokerto University.  Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8933 10.31315/telematika.v20i1.8933 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 129-138 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 129-138 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8933/5403 10.31315/telematika.v20i1.8933.g5403 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/8959 2025-12-09T08:39:35Z telematika:GEN driver

Forecasting Sea Surface Salinity in the Eastern Madura Strait Using a 1D Convolutional Neural Network Rozzy, Fahrul Novitasari, Dian Candra Rini Yuliati, Dian Sani, Puteri Permata 1D-CNN Forecasting Salinity Tujuan: Penelitian ini bertujuan untuk memprediksi salinitas permukaan air laut pada perairan Selat Madura bagian Timur menggunakan 1D CNN dan menguji daripada performa model arsitektur 1D CNN yang dibuat. Berdasarkan hasil prediksi yang diperoleh, diharapkan mampu memberi informasi ke masyarakat terkait kondisi salinitas permukaan Selat Madura bagian Timur beberapa hari ke depan.Perancangan/metode/pendekatan: Hal pertama yang perlu dilakukan adalah memprediksi tiap parameter sebelum memprediksi salinitas permukaan. Penelitian ini menggunakan metode 1D CNN, dengan parameter kecepatan arus eastward, arus northward dengan 3 kedalaman berbeda, dan salinitas pada 2 kedalaman berbeda.Hasil: Berdasarkan penelitian ini diperoleh model 1D CNN mampu memprediksi salinitas dengan sangat baik, dengan MAPE sebesar 2.86% pada nilai dropout 0.8 dan batchsize 64. Adapun hasil prediksi untuk 6 hari ke depan, dari 17 Januari 2023 pukul 19.00 hingga 23 Januari 2023 pukul 07.00 dengan rentang waktu per 12 jam adalah mengalami penurunan dengan angka terendah menyentuh 33.313 PSU.Keaslian/ state of the art: Pada penelitian ini menggunakan parameter prediksi, metode, dan diperoleh hasil yang berbeda dengan penelitian sebelumnya. Jurusan Informatika 2024-06-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8959 10.31315/telematika.v21i1.8959 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 21 No. 1 (2024): Edisi Pertama 2024; 14-30 Telematika; Vol 21 No 1 (2024): Edisi Pertama 2024; 14-30 2460-9021 1829-667X 10.31315/telematika.v21i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/8959/6342 10.31315/telematika.v21i1.8959.g6342 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi https://creativecommons.org/licenses/by-nc-sa/4.0

oai:jurnal.upnyk.ac.id:article/9044 2024-12-02T00:49:15Z telematika:GEN driver

Sentiment Analysis of Cryptocurrency Exchange Application on Twitter Using Naïve Bayes Classifier Method Indarso, Andhika Octa Irmanda, Helena Nurramdhani Astriatma, Ria naïve bayes indodax tokocrypto twitter analisis sentimen Purpose: The growth and development of the digital currency industry also presents a variety of applications for conducting transactions using these currencies, including utilizing cryptocurrency exchanges to make investments. InI ndonesia, there are two applications that fall into the category of the largest cryptocurrency exchange and are recognized by Bappebti (Commodity Futures Trading Regulatory Agency), namely TokoCrypto and Indodax. Both applications are analyzed based on the sentiments of their users on Twitter.Design/methodology/approach: In this study the data collected is data originating from social media Twitter and has the keywords "indodax" or "#indodax" and "tokocrypto" or "#tokocrypto". The data used is between January 2021 – January 2022. The data collected from Twitter is processed using the Naïve Bayes Classifier algorithm.Findings/result: From the results of the analysis, it was found that the Indodax application has a higher positive sentiment percentage value of 9% compared to TokoCrypto.Originality/value/state of the art: The use of the Naïve Bayes algorithm in this study supports sentiment analysis of cryptocurrency exchange application users to consider which application has better positive sentiment for investing in digital currency or cryptocurrency. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9044 10.31315/telematika.v20i1.9044 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 15-30 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 15-30 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9044/5397 10.31315/telematika.v20i1.9044.g5397 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9161 2024-12-02T00:49:17Z telematika:GEN driver

Human Skin Disease Detection using Convolutional Neural Network Method with Hyperparameter Tuning to Determine the Best Parameter Combination Aritonang, Riki Martua Florestiyanto, Mangaras Yanu Yuwono, Bambang Hyperparameter Tuning Skin Disease CNN Purpose: Obtaining the best hyperparameter combination for optimization of the Convolutional Neural Network method, for classifying skin diseases.Design/methodology/approach: Using the CNN method with hyperparameter tuning in determining the best hyperparameter combination. System development is performed with the Python programming language.Findings/result: The best combination of hyperparameter tuning results is RMSprop optimizer, APL dropout value is 0.05, dropout is 0.5 , dense layer is 64, and produces an accuracy of 97,81%.Originality/value/state of the art: This study has differences in terms of the types of skin diseases classified, the architecture of the CNN model, the hyperparameters tested and the combination results obtained compared to previous studies. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9161 10.31315/telematika.v20i2.9161 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 215-225 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 215-225 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9161/5666 10.31315/telematika.v20i2.9161.g5666 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9329 2024-12-02T00:49:16Z telematika:GEN driver

Performance Analysis of XGBoost Algorithm to Determine the Most Optimal Parameters and Features in Predicting Stock Price Movement Ardana, Affan machine learning regresi prediksi saham xgboost Purpose: The research aims to find the best parameters and features for predicting stock price movement using the XGBoost algorithm. The parameters are searched using the RMSE value, and the features are searched using the importance value.Design/methodology/approach: The research data is the stock data of Amazon.com company (AMZN). The dataset contains the Date, Low, Open, Volume, High, Close, and Adjusted Close features. The dataset is ensured to have no missing data by handling missing values. The input feature is selected using the Pearson Correlation feature selection method. To prevent the difference between the highest and lowest stock price from being too far apart, the data is scaled using the scaling method. To avoid bias that may appear in the prediction result, cross-validation is used with the Min Max Scaling method, which will devide the dataset into training data and testing data within a range of 30 days after the training data. The parameters to be tested include n_estimator = 500, early stopping round = 3, learning rate = 0.01, 0.05, 0.1, and max_depth (tree depth) = 3, 4, 5.Findings/result: The result of the research that a learning rate of 0.05 and a tree depth of 5 obtained the lowest RMSE result compared to other models, with an RMSE of 0.009437. The Low feature obtained the highest importance value among all the models built.Originality/value/state of the art: This study used testing data within a range of 30 days after the training data and used a combination of parameters, including n_estimator = 500, early stopping round = 3, learning rate = 0.01, 0.05, 0.1, amd max_depth (tree depth) = 3, 4, 5.  Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9329 10.31315/telematika.v20i1.9329 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 91-102 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 91-102 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9329/5411 10.31315/telematika.v20i1.9329.g5411 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9358 2024-12-02T00:49:16Z telematika:GEN driver

Application of Expert System Identification of Horticultural Plant Diseases with Certainty Factor and Forward Chaining for Smart Village Concept Development Wicaksono, Damar Adi Nata, Imam Expert System diagnosing plants Purpose: This research was conducted to help identify diseases early and provide suggestions for recommendation systems for these plants in general that are beneficial for farmers.Design/methodology/approach: This research goes through several stages, namely planning , analysis, design, and implementation.Findings/result: CLIPS-based Horticultural Plant Disease Identification Expert SystemOriginality/value/state of the art: In the process of diagnosing plant diseases, it requires the accuracy and thoroughness of an expert or experts on symptoms that indicate a disease because of the similarity of these symptoms. Misdiagnosis of existing symptoms causes differences in the results of the diagnosis with the actual disease suffered by the plant. Along with the development of technology, a system was devised that would help report early identification of diseases and provide suggestions for recommendation systems for these plants in general that are beneficial to farmers. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9358 10.31315/telematika.v20i1.9358 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 63-80 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 63-80 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9358/5412 10.31315/telematika.v20i1.9358.g5412 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9444 2024-12-02T00:49:18Z telematika:GEN driver

Sensitivity Comparison of AHP with The Combination of AHP and SAW for Facial Wash Recommendation System based on Skin Type Charibaldi, Novrido Hanifah, Qurrotu'ain Perwira, Rifki Indra Decision Support System Analytical Hierarchy Process Simple Additive Weighting sensitivity comparison facial wash recommendation Purpose: This research aims to design a facial wash recommendation system based on all skin types, namely normal, dry, oily, combination, and sensitive. This is to tackle the limitation of previous systems that were developed based on limited skin types which are normal, dry, and oily using Promethee II, Fuzzy Logic, and SAW methods.Design/methodology/approach: This research uses the Analytic Hierarchy Process (AHP) method and a combination of AHP and Simple Additive Weighting (SAW) to consider the importance values of each criterion. Four criteria data are used, namely price, rating, content, and availability, along with 70 alternative data of facial wash products.Finding/Result: Sensitivity testing was conducted on both methods, and the combination of AHP and SAW produced a higher sensitivity percentage, which is 67.51%, whereas the AHP method provided a lower sensitivity percentage of 59.26%.Originality/state of the art: The combination of AHP and SAW is an innovation in designing a facial wash recommendation system, and the research results demonstrate that the combination of AHP and SAW is a superior method for recommending facial wash products. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9444 10.31315/telematika.v20i2.9444 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 283-294 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 283-294 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9444/5709 10.31315/telematika.v20i2.9444.g5709 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9518 2024-12-02T00:49:15Z telematika:GEN driver

Implementation of Mel-Frequency Cepstral Coefficient as Feature Extraction using K-Nearest Neighbor for Emotion Detection Based on Voice Intonation Nawasta, Revanto Alif Cahyana, Nur Heri Heriyanto, Heriyanto Mel-Frequency Cepstral Coefficient K-Nearest Neighbor Emotion detection Signal processing Purpose: To determine emotions based on voice intonation by implementing MFCC as a feature extraction method and KNN as an emotion detection method.Design/methodology/approach: In this study, the data used was downloaded from several video podcasts on YouTube. Some of the methods used in this study are pitch shifting for data augmentation, MFCC for feature extraction on audio data, basic statistics for taking the mean, median, min, max, standard deviation for each coefficient, Min max scaler for the normalization process and KNN for the method classification.Findings/result: Because testing is carried out separately for each gender, there are two classification models. In the male model, the highest accuracy was obtained at 88.8% and is included in the good fit model. In the female model, the highest accuracy was obtained at 92.5%, but the model was unable to correctly classify emotions in the new data. This condition is called overfitting. After testing, the cause of this condition was because the pitch shifting augmentation process of one tone in women was unable to solve the problem of the training data size being too small and not containing enough data samples to accurately represent all possible input data values.Originality/value/state of the art: The research data used in this study has never been used in previous studies because the research data is obtained by downloading from Youtube and then processed until the data is ready to be used for research. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9518 10.31315/telematika.v20i1.9518 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 51-62 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 51-62 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9518/5400 10.31315/telematika.v20i1.9518.g5400 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9575 2024-12-02T00:49:16Z telematika:GEN driver

Implementation of Web Scraping on Google Search Engine for Text Collection Into Structured 2D List Fahrudin, Tresna Maulana Riyantoko, Prismahardi Aji Hindrayani, Kartika Maulida web scraping google search engine text collection structure of 2D list parsing HTML Purpose: This research proposes the implementation of web scraping on Google Search Engine to collect text into a structured 2D list.Design/methodology/approach: Implementing two important stages in the process of collecting data through web scraping, namely the HTML parsing process to extract links (URL) on Google Search Engine pages, and HTML parsing process to extract the body text from website pages on each link that has been collected.Findings/result: The inputted query is adjusted to the latest issues and news in Indonesia, for example the President's important figures, the month of Ramadan and Idul Fitri, riots tragedy (stadium) and natural disasters, rising prices of basic commodities, oil and gold, as well as other news. The least number of links obtained was 56 links and the most was 151 links, while the processing time to obtain links for each of the fastest queries was 1 minute 6.3 seconds and the longest was 2 minutes 49.1 seconds. The results of scraping links from these queries were obtained from Wikipedia, Detik, Kompas, the Election Supervisory Body (Bawaslu), CNN Indonesia, the General Election Commission (KPU), Pikiran Rakyat, and others.Originality/value/state of the art: Based on previous research, this study provides an alternative to produce optimal collection of links and text from web scraping results in the form of a 2D list structure. Lists in the Python programming language can store character sequences in the form of strings and can be accessed using index keys, and manipulate text efficiently. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9575 10.31315/telematika.v20i2.9575 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 139-152 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 139-152 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9575/5536 10.31315/telematika.v20i2.9575.g5536 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9642 2024-12-02T00:49:17Z telematika:GEN driver

Systematic Literature Review on Information Technology Governance in Government Wicaksono, Januar Agung Widodo, Aris Puji Adi, Kusworo Public Governance Information Technology Artificial Intelligence Purpose: This article aims to assist the government in developing better, more efficient, and sustainable public governance by utilizing information technology and artificial intelligence. The article provides insights on how information technology and artificial intelligence can be applied in public governance to improve the efficiency, effectiveness, and sustainability of public services, as well as to enhance public trust in the government.Design/Method/Approach: The method used in this article is a Systematic Literature Review (SLR), which is a systematic and methodological research method for collecting, evaluating, and synthesizing evidence from previous studies in the field under investigation, through search terms and searching for information in online databases and creating inclusion and exclusion criteria.Results: This article is expected to achieve more efficient, effective, and sustainable public governance and improve the quality of public services and public trust. The article also shows that information technology and artificial intelligence have become an integral part of public governance in various countries, with many countries taking a holistic and sustainable approach.Originality/State of the art: The state-of-the-art of this article is that information technology and artificial intelligence can be effectively used to improve public governance to achieve better, more efficient, and sustainable goals. The article also emphasizes the importance of considering data privacy, cyber security, and unwanted environmental impacts, as well as considering ethical and human rights aspects in the development of artificial intelligence. This will help the government to develop and implement information technology and artificial intelligence in public governance in a responsible and sustainable manner. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9642 10.31315/telematika.v20i2.9642 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 226-237 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 226-237 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9642/5667 10.31315/telematika.v20i2.9642.g5667 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9645 2024-12-02T00:49:15Z telematika:GEN driver

Retinal Vessel Segmentation to Support Foveal Avascular Zone Detection Dharmawan, Dhimas Arief Purpose: This study aims to perform retinal vessel segmentation to support foveal avascular zone detection. Methodology: The proposed approach consists of a multi-stage image processing approach, including preprocessing, image quality enhancementt, and segmentation of retinal blood vessel using matched filter and length filter techniques.Findings: The proposed framework has achieved remarkable results with an average sensitivity, specificity, and accuracy of 77.99%, 86.43%, and 85.24%, respectively.Value: This achievement has the potential to significantly enhance the accuracy and efficiency of detecting and diagnosing medical conditions related to the retina, improving the quality of life for countless individuals. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9645 10.31315/telematika.v20i1.9645 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 41-50 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 41-50 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9645/5399 10.31315/telematika.v20i1.9645.g5399 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9674 2024-12-02T00:49:16Z telematika:GEN driver

Input Variable Selection for Oil Palm Plantation Productivity Prediction Model Suryotomo, Andiko Putro Harjoko, Agus IVS oil palm expert knowledge Purpose: This study aims to implement and improve a wrapper-type Input Variable Selection (IVS) to the prediction model of oil palm production utilizing oil palm expert knowledge criteria and distance-based data sensitivity criteria in order to measure cost-saving in laboratory leaf and soil sample testing.Methodology: The proposed approach consists of IVS process, searching the best prediction model based on the selected variables, and analyzing the cost-saving in laboratory leaf and soil sample testing.Findings/result: The proposed method managed to effectively choose 7 from 19 variables and achieve 81.47% saving from total laboratory sample testing cost.Value: This result has the potential to help small stakeholder oil palm planter to reduce the cost of laboratory testing without losing important information from their plantation. Jurusan Informatika 2023-03-01 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9674 10.31315/telematika.v20i1.9674 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 1 (2023): Edisi Februari 2023; 103-116 Telematika; Vol 20 No 1 (2023): Edisi Februari 2023; 103-116 2460-9021 1829-667X 10.31315/telematika.v20i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9674/5617 10.31315/telematika.v20i1.9674.g5617 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9676 2024-12-02T00:49:17Z telematika:GEN driver

Preprocessing Using SMOTE and K-Means for Classification by Logistic Regression on Pima Indian Diabetes Dataset Akbar, Ahmad Taufiq Husaini, Rochmat Prapcoyo, Hari SMOTE k-means Logistic Regression Purpose: Our study aims to combine pre-processing methods to develop a training data model from the Indian diabetic Pima dataset so that it can improve the performance of machine learning in recognizing diabetesDesign/methodology/approach: This research was started through several stages such as collecting the Pima indian diabetes dataset, pre-processing including k-means clustering, oversampling using SMOTE, then undersampling the dataset whose cluster is a minority in each class. Furthermore, the dataset is classified using machine learning namely logistic regression through 10 cross validationFindings/result: The results of this classification performance show that the accuracy reaches 99.5% and is higher than the method in previous studies.Originality/value/state of the art:The method in this study uses SMOTE to handle data imbalances and k-means clustering to remove outliers by removing labels that do not match the majority cluster in each class so that clean data is produced and validation using logistic regression is more accurate than previous studies.Tujuan: Penelitian ini bertujuan untuk menerapkan metode pre-processing untuk membentuk model data latih dari dataset Pima Indian diabetes sehingga dapat meningkatkan performa mesin pembelajaran dalam mengenali diabetes.Perancangan/metode/pendekatan: Riset ini dimulai melalui beberapa tahap yakni pengumpulan dataset Pima Indian diabetes, pre-processing meliputi clustering, oversampling menggunakan SMOTE, kemudian undersampling pada dataset pada klaster  minoritas pada setiap kelas. Selanjutnya dataset diklasifikasikan menggunakan machine learning yakni metode regresi logistik melalui 10 cross validationHasil: Hasil dari performa klasifikasi ini menunjukkan akurasi mencapai 99,5% dan lebih tinggi daripada metode pada penelitian sebelumnya.Keaslian/ state of the art: Metode dalam penelitian ini menggunakan SMOTE untuk menangani ketidakseimbangan data dan k-means klastering untuk membuang outlier dengan cara menghapus label yang tidak sesuai dengan klaster mayoritas pada setiap kelas sehingga dihasilkan data yang bersih dan pada validasi menggunakan logistic regression lebih akurat daripada penelitian sebelumnya. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9676 10.31315/telematika.v20i2.9676 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 238-249 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 238-249 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9676/5669 10.31315/telematika.v20i2.9676.g5669 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9820 2025-12-09T08:39:05Z telematika:GEN driver

Tweet Analysis of Mental Illness Using K-Means Clustering and Support Vector Machine Kusumaningtyas, Kartikadyota Habibi, Muhammad Dwijayanti, Irmma Sumiyarini, Retno Sentiment Analysis Clustering Mental Illness Purpose: Social media, particularly Twitter, provides a venue for individuals to share their thoughts. The public's perception of mental illnesses is often debated on Twitter. So yet, no evaluation of community tweets connected to data on mental health conditions has been performed. The purpose of this study is to examine tweets linked to mental illnesses in Indonesia in order to identify the themes of conversation and the polarity trends of these tweets.Design/methodology/approach: To address this issue, the K-Means Clustering algorithm is utilized to aggregate tweet data that is used to find themes of conversation. The emotion polarity value of each cluster result was then determined using the Support Vector Machine (SVM) approach.Findings/results: This study generated five topic clusters based on tweets about mental illness. While sentiment analysis revealed that all clusters had more negative sentiment classes than positive. Cluster 4 and Cluster 5 had the highest number of negative sentiment values. These clusters emphasize the necessity of consulting with psychiatrists and psychologists if people have mental health disorders, as well as financing for mental health disorder treatment through BPJS Kesehatan services.Originality/value/state of the art: The analysis was done in two stages: data grouping to find themes of conversation using K-Means clustering and SVM to look for positive and negative polarity values associated to twitter data about mental illness. Jurusan Informatika 2023-11-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9820 10.31315/telematika.v20i3.9820 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 3 (2023): Edisi Oktober 2023; 295-308 Telematika; Vol 20 No 3 (2023): Edisi Oktober 2023; 295-308 2460-9021 1829-667X 10.31315/telematika.v20i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9820/6207 10.31315/telematika.v20i3.9820.g6207 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9830 2025-12-09T08:39:05Z telematika:GEN driver

Performance Evaluation of Online Smart Parking System in Jakarta Suhada, Suhada Hendriana, Yana Application Smart Parking System Evaluation Purpose: This research aims to evaluate the performance of the Online Smart Parking System application for 7 consecutive days from 06.00 to 18.00 to evaluate the features in the application, evaluate the level of compliance of the clerks with the use of the application and the level of constraints achievement or fulfillment of each of the rights and obligations of the parties, and identification of the level of achievement of revenue targets.Design/methodology/approach: This research was carried out through several stages which include Product Quality Evaluation, Usage Quality Evaluation, Collaboration Evaluation and Financial Evaluation or financial aspects.Findings/result: Design of Logical Framework Application System Online Smart Parking System.Originality/value/state of the art: This research focuses on evaluating the design results of the Online Smart Parking System application which is managed by UP Parking Department of Transportation DKI Jakarta with 3 partner applicators. Jurusan Informatika 2023-11-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9830 10.31315/telematika.v20i3.9830 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 3 (2023): Edisi Oktober 2023; 309-325 Telematika; Vol 20 No 3 (2023): Edisi Oktober 2023; 309-325 2460-9021 1829-667X 10.31315/telematika.v20i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9830/6208 10.31315/telematika.v20i3.9830.g6208 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/9861 2025-12-09T08:39:35Z telematika:GEN driver

Strawberry Fruit Disease Identification Using Digital Image Processing Using GLCM With Artificial Neural Network Method Wardaya, Imanuel Puspa Hermawan, Arief Artificial Neural Network GLCM Strawberry Disease Detection Backpropagation Purpose: This research aims to identify strawberry fruit diseases using digital image processing using GLCM with the backpropagation artificial neural network method.Design/methodology/approach: Using images that have been preprocessed grayscale, crop, and resize and then processed using GLCM for traning using backpropagation artificial neural networks.Findings/result: Based on 250 image data that is processed by GLCM and classified using a backpropagation artificial neural network, it can be concluded that the best accuracy rate is obtained from ReLU activation with a traning data accuracy value of 95% and test data accuracy of 54%.Originality/value/state of the art: This research uses a combination of primary data with kaggle data by using a comparison of several experiments by changing the loss, optimizer and activation parameters. Jurusan Informatika 2024-02-21 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9861 10.31315/telematika.v21i1.9861 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 21 No. 1 (2024): Edisi Pertama 2024; 80-91 Telematika; Vol 21 No 1 (2024): Edisi Pertama 2024; 80-91 2460-9021 1829-667X 10.31315/telematika.v21i1 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/9861/6672 10.31315/telematika.v21i1.9861.g6672 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi https://creativecommons.org/licenses/by-nc-sa/4.0

oai:jurnal.upnyk.ac.id:article/10009 2024-12-02T00:49:17Z telematika:GEN driver

The Implementation of Color Feature Extraction and Gray Level Co-occurrence Matrix Combination in K-Nearest Neighbor Classification Method for Tomato Leaf Disease Identification Agusta, Sandy Wahyu Kaswidjanti, Wilis Classification K-Nearest Neighbor RGB HSV GLCM Purpose: Tomato plants are quite important commodities in Indonesia. With a complete and good content of substances, tomatoes become a product that is widely consumed by the public. However, much of the decline in crop production is caused by plant disruptive organisms such as viruses and bacteria. Early identification of plant diseases is expected to prevent the spread of diseases caused by these organisms.Design/methodology/approach: In this study the data used in machine training are data from kaggle sites. This study uses the K-Nearest Neighbor classification method with a combination method of extracting feature on RGB, HSV and GLCM images to obtain the best accuracy value.Findings/Results: Based on the test results among the combination methods of feature extraction in the process of identifying tomato leaf diseases which are classified into 7, namely testing units of RGB, HSV, GLCM followed by a combination of RGB HSV, RGB GLCM, HSV GLCM, and RGB HSV GLCM methods obtained a comparison value of 71.5%, 72.9%, 79%, 82.5%, 90.6%, 87.4% and 87.7%. Based on these data, it was concluded that with the combination of the RGB GLCM method obtained the best accuracy value in the identification of tomato leaf disease with an accuracy rate of 90.6%.Originality/value/state of the art: The use of the K-Nearest Neighbor classification method in this study combines the collection of selected characteristics so as to get a comparison of 7 combination groups between RGB, HSV, and GLCM. Jurusan Informatika 2023-06-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/10009 10.31315/telematika.v20i2.10009 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 2 (2023): Edisi Juni 2023; 250-262 Telematika; Vol 20 No 2 (2023): Edisi Juni 2023; 250-262 2460-9021 1829-667X 10.31315/telematika.v20i2 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/10009/5670 10.31315/telematika.v20i2.10009.g5670 Copyright (c) 2023 Telematika : Jurnal Informatika dan Teknologi Informasi

oai:jurnal.upnyk.ac.id:article/10096 2025-12-09T08:39:05Z telematika:GEN driver

Design of a Generative AI Image Similarity Test Application and Handmade Images Using Deep Learning Methods Prawiratama, Rifqi Alfaesta Deep Learning AI Generative Transformers BEiT Image Classification Purpose: The aim of this research is to develop a classification model using the Transformer approach, specifically the BEiT architecture, to differentiate between handmade images and AI Generative Art. The objective is to ensure the authenticity of art and address ethical and legal concerns related to AI Generative Art.Design/methodology/approach: The study utilizes the BEiT architecture within the Transformer approach to create a classification model. The training process uses Bidirectional Encoder representation from Image Transformers (BEiT) to improve image classification. The primary datasets are collected through a Python image scraper program. The BEiT workflow includes Pre-training, Masking, Inpainting, and Interface Design with Gradio.Findings/result: The Transformer model, using the BEiT architecture, achieves 96.34% accuracy and 0.0921 loss in differentiating handmade images and AI Generative Art. The model demonstrates a balanced precision and recall in each category, outperforming previous methods such as Convolutional Neural Network (CNN) and VGG16. The language used is clear, objective, and value-neutral, with a formal register and precise word choice. No changes in content were made. The Gradio interface was used to successfully test the model.Originality/value/state of the art: The research presents a state-of-the-art classification model that uses the Transformer approach, specifically the BEiT architecture, to differentiate between handmade and AI Generative Art images. The research presents a state-of-the-art classification model that uses the Transformer approach, specifically the BEiT architecture, to differentiate between handmade and AI Generative Art images. The text adheres to conventional structure and formatting features, including consistent citation and footnote style. The sentences and paragraphs create a logical flow of information with causal connections between statements. The text is free from grammatical errors, spelling mistakes, and punctuation errors. Additionally, the research is enhanced by the innovative approach to data collection using a Python image scraper program. Jurusan Informatika 2023-11-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://jurnal.upnyk.ac.id/index.php/telematika/article/view/10096 10.31315/telematika.v20i3.10096 Telematika: Jurnal Informatika dan Teknologi Informasi; Vol. 20 No. 3 (2023): Edisi Oktober 2023; 326-342 Telematika; Vol 20 No 3 (2023): Edisi Oktober 2023; 326-342 2460-9021 1829-667X 10.31315/telematika.v20i3 eng https://jurnal.upnyk.ac.id/index.php/telematika/article/view/10096/6206 10.31315/telematika.v20i3.10096.g6206 Copyright (c) 2024 Telematika : Jurnal Informatika dan Teknologi Informasi f163e968246247f5913353540b6423f8