Poultry Disease Detection Simulation using Case-Based Reasoning based on Nearest Neighbor Retrieval

Ivana Puspita Sari, Isna Nur Aini, Satya Ghifari Adipratama, Shoffan Saifullah

Abstract


Tujuan: Mendeteksi penyakit unggas (ayam) dan memberikan solusi alternatif dengan simulasi sistem. Sehingga dapat memberikan kontribusi dalam pengembangan teknologi bidang peternakan.
Perancangan/metode/pendekatan: Penelitian ini menggunakan metode Case-Based Reasoning (CBR). Metode CBR menggunakan rule-based dalam penyelesaian masalah (khususnya deteksi penyakit ayam). Selain itu,  retrieve pada CBR menggunakan metode Nearest Neighbor Retrieval dalam mencari kemiripan berdasarkan bobot yang diberikan. Hasil: Simulasi sistem mampu mendeteksi penyakit unggas dengan nilai similarity kasus percobaan yang diujikan sebesar 69,3% dan percobaan gejala lain memiliki similarity sebesar 99.9%. Hal ini ditunjukkan dalam proses deteksi sistem dan perhitungan perhitungan manualnya. Keaslian/ state of the art: Penelitian ini menggunakan CBR-Nearest Neighbor Retrieval berdasarkan rule dan kemiripan kasus yang ada.


Keywords


Poultry disease detection; Expert system simulation; Case-based reasoning, Nearest neighbor retrieval

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References


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