Sistem Pakar Diagnosa Penyakit Kambing Menggunakan Metode Backward Chaining

Health problems in livestock often become a major obstacle for goat farmers, especially when the symptoms of diseases are noticed late. In Siak Kecil District itself, many farmers face difficulties due to limited access to veterinary professionals and minimal literacy regarding types of goat diseases. Based on this issue, this study develops a digital solution in the form of a web-based expert system designed to help farmers conduct self-diagnosis using the Backward Chaining method. Technically, this method works by testing disease hypotheses through the symptoms experienced by livestock, similar to the way a veterinarian thinks during an examination. The application, named "Goat Diagnosa," is built using the PHP programming language with the Laravel framework and implements the Rapid Application Development (RAD) model. This system integrates a knowledge base covering 9 types of diseases and 35 symptoms that have been validated by experts. Based on testing on 24 case scenarios, the system achieved an accuracy rate of 91.6%. The presence of this tool is expected to serve as a digital assistant for farmers in performing early detection, thereby minimizing the risk of livestock death due to delayed treatment.