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

Doms Upuy, Citra Fathia Palembang

Abstract


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

Keywords


Tuberculosis; Clustering; K-Means

Full Text:

PDF

References


G. A. Azwar, D. I. Noviana, and F. Hendriyono, “Karakteristik Penderita Tuberkulosis Paru Dengan Multidrug-Resistant Tuberculosis (Mdr-Tb) Di Rsud Ulin Banjarmasin,” Berk. Kedokt., vol. 13, no. 1, p. 23, 2017, doi: 10.20527/jbk.v13i1.3436.

N. A. Albaihaqi, B. Burhanuddin, and V. Z. Latuconsina, “Karakteristik Pasien Tuberkulosis Paru Dengan Multidrug-Resistant (Tb Mdr) Di Rsud Dr. M. Haulussy Ambon Tahun 2014-2018,” PAMERI Pattimura Med. Rev., vol. 2, no. 2, pp. 90–102, 2021, doi: 10.30598/pamerivol2issue2page90-102.

L. Parera, S. Hadisaputro, and D. T. H. Lukmono, “EVALUASI PROGRAM PENGENDALIAN TUBERCULOSIS DI WILAYAH KERJA PUSKESMAS (Studi di Kota Ambon),” Care J. Ilm. Ilmu Kesehat., vol. 8, no. 3, p. 383, 2020, doi: 10.33366/jc.v8i3.1266.

Susi Susanti and K. Handoko, “Penerapan Data Mining Analisa Penyakit Menular Pada Manusia,” J. Comasie, vol. 05, no. 07, 2021.

C. F. Palembang and S. P. Palembang, “PROVINSI DI INDONESIA MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING ( Grouping Chillies Price Levels Based On Province In Indonesia Using K-Means Clustering Algorithm ),” vol. 3, pp. 48–60, 2021.

Z. Nabila, “Analisis Data Mining Untuk Clustering Kasus Covid-19,” J. Teknol. dan Sist. Inf., vol. 2, no. 2, pp. 100–108, 2021.

T. Rachman, “Penerapan Aplikasi RapidMiner Untuk Prediksi Nilai Tukar Rupiah Terhadap US Dollar Dengan Metode Regresi Linier,” Angew. Chemie Int. Ed. 6(11), 951–952., pp. 10–27, 2018.

I. N. M. Adiputra, “Clustering Penyakit Dbd Pada Rumah Sakit Dharma Kerti Menggunakan Algoritma K-Means,” Inser. Inf. Syst. Emerg. Technol. J., vol. 2, no. 2, p. 99, 2022, doi: 10.23887/insert.v2i2.41673.

P. M. Silitonga Irene Sri, “Klusterisasi Pola Penyebaran Penyakit Pasien Berdasarkan Usia Pasien Dengan Menggunakan K-Means Clustering,” J. TIMES, vol. VI, no. Vol 6, No 2 (2017), pp. 22–25, 2017, [Online]. Available: http://ejournal.stmik-time.ac.id/index.php/jurnalTIMES/article/view/584.

Ediyanto, N. Mara, and N. Satyahadewi, “Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis,” Bul. Ilm. Mat. Stat. dan Ter., vol. 02, no. 2, pp. 133–136, 2013.




DOI: https://doi.org/10.31315/telematika.v19i3.7709

DOI (PDF): https://doi.org/10.31315/telematika.v19i3.7709.g4754

Refbacks



Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Copyright of :
TELEMATIKA: Jurnal Informatika dan Teknologi Informasi
ISSN 1829-667X (print); ISSN 2460-9021 (online)


Dipublikasi oleh
Jurusan Teknik Informatika, UPN Veteran Yogyakarta
Jl. Babarsari 2 Yogyakarta 55281 (Kampus Unit II)
Telp: +62 274 485786
email: jurnaltelematika@upnyk.ac.id

 

Jurnal Telematika sudah diindeks oleh beberapa lembaga berikut:
 

 

 

 

 

Status Kunjungan Jurnal Telematika
slot gacor slot