The The pig population in North Central Timor (TTU) Regency in 2025 reached 111,704, making pig farming one of the main sources of livelihood for the local community. However, farmers often experience substantial losses due to high livestock mortality rates during disease outbreaks. This situation is largely attributed to the limited knowledge of pig farmers regarding disease symptoms and types, as well as limited access to information on early disease management. This study aims to develop a pig disease diagnostic application capable of identifying disease types based on observable symptoms and providing recommendations for initial treatment and preventive measures. The application was developed using the Rapid Application Development (RAD) method to accelerate system design and implementation. Meanwhile, the Forward Chaining method was applied as a fact-finding technique to infer accurate conclusions regarding disease types based on symptoms. The results of this study include a web-based pig disease diagnostic application that implements symptom tracking using forward chaining, enabling farmers to independently identify pig diseases more quickly and accurately. The developed application is expected to help reduce pig mortality rates and improve the efficiency of livestock production, particularly pig farming in TTU Regency.
Copyrights © 2025