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Andika Eka Putra
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Implementasi Metode Bayesian Network Untuk Diagnosis Penyakit Kambing (Studi Kasus : UPTD Pembibitan Ternak dan Hijauan Makanan Ternak Singosari Malang) Andika Eka Putra; Nurul Hidayat; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 9 (2018): September 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Infectious disease factors are serious constraints that farmers should be aware of especially for traditional farmers who do not join livestock groups. Slow and improper handling can endanger livestock conditions. However, if the initial treatment is done, the chances of infection of the disease can be handled so as not to be more severe and contagious to other goats in a herd. Unfortunately, the uncertainty between the symptoms and the type of disease makes the farmers obstructed in the initial treatment, and do not know what to do without an expert. Based on these problems, the authors make a system of diagnosis of goat disease that is able to perform the diagnosis process based on the symptoms of goat. This diagnostic system uses Bayesian network method, the system is built on mobile device applications using the Android platform as the user interface, while the calculation process using PHP programming language, and MySQL database to store the prevalence of goat disease that has occurred. This system through the process of system functional testing and system accuracy testing. In the process of testing the functionality of this diagnostic system shows the functions that exist on the system goes well. In addition, the process of accuracy testing of goat disease diagnosis system using Bayesian Network method is done by entering the variation of symptoms by experts get the result of 86.6%.
Co-Authors Imam Cholissodin Nurul Hidayat