Sistem Pakar Diagnosis Penyakit Ternak Sapi Berbasis Website Menggunakan Forward Chaining dengan Integrasi Fuzzy Logic pada Dinas Peternakan Kabupaten Muna - Suci Wulandari; Bambang Pramono; Adha Mashur Sajiah; Isnawaty . (CV. Information Technology Training Center - Indonesia (ITTC), 2026)
Cattle are livestock with high economic value for the people of Muna Regency, serving not only as a source of food but also as productive assets that contribute significantly to the regional economy. However, diagnosing diseases in cattle remains a major challenge because many diseases exhibit similar and non-specific symptoms, making early identification difficult. This condition often results in delayed treatment, reduced livestock productivity, and economic losses for farmers. This study aims to develop an expert system that can assist farmers and animal health officers in diagnosing cattle diseases accurately and efficiently by integrating the Forward Chaining and Fuzzy Logic methods to improve the reliability of the diagnostic process under uncertain symptom conditions. The research employed a system development approach consisting of literature review, knowledge acquisition, system design, implementation, and testing. The system integrates the Forward Chaining method for rule-based reasoning and Fuzzy Logic to manage uncertainty in symptom values. The analysis techniques used include Black Box Testing to evaluate system functionality and accuracy testing by comparing the system's diagnostic results with expert diagnoses. The results show that the developed expert system functions properly according to its design specifications and produces consistent and reliable diagnostic results. The combination of Forward Chaining and Fuzzy Logic improves diagnostic accuracy by effectively handling uncertain symptom data, making the system a useful decision-support tool for early detection and management of cattle diseases in Muna Regency.