Sistem Pakar Diagnosis Penyakit Ayam Petelur Program Gayatri Menggunakan Certainty Factor dan Chatbot AI Berbasis Web
Abstract
Limited access to information and expert assistance in identifying diseases in laying hens can hinder early diagnosis and disease management among farmers participating in the Gayatri Program in Bojonegoro Regency. This study aims to develop a web-based expert system to support the early diagnosis of diseases in laying hens using the Certainty Factor (CF) method and to provide an AI chatbot as an additional consultation medium. The developed system, TANGKAS, utilizes a knowledge base consisting of 7 diseases and 18 clinical symptoms. The CF method employs Measure of Belief (MB) and Measure of Disbelief (MD) values to determine the level of confidence in a disease based on symptoms provided by users. The system was developed using the Waterfall method and evaluated through Black Box Testing, White Box Testing, diagnostic accuracy testing, and User Acceptance Testing (UAT). Testing on 46 cases showed that 42 cases produced diagnoses consistent with the comparison results, resulting in an accuracy rate of 91.30%. UAT involving 30 respondents yielded an acceptance score of 82.53%, categorized as highly feasible. The contribution of this study lies in integrating CF as the diagnostic inference engine with an AI chatbot based on a Large Language Model as an additional consultation medium within a single web-based system to support early diagnosis and provide health information for laying hens in the Gayatri Program.
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References
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