Integrasi Metode Forward Chaining dan Teorema Bayes Untuk Identifikasi Diagnosa Penyakit Kulit Pada Kucing - Anugerah, Ade; Sucipto, Sucipto; Agustini Alkadri, Syarifah Putri (Unversitas Muhammadiyah Riau, 2025)
Skin diseases in cats are among the most common health issues, yet many cat owners still lack awareness of their symptoms. Limited access to veterinary services, especially in regions such as West Kalimantan, poses a significant challenge in early identification and treatment. This study aims to develop a web-based expert system capable of automatically diagnosing skin diseases in cats based on symptoms inputted by users. The system utilizes the Forward Chaining method for rule-based inference and the Bayes Theorem for probabilistic calculation to determine the likelihood of diseases. The system was built using the Laravel framework and MySQL database, based on a total of 83 case data obtained through direct interviews with veterinary experts. Testing using black-box and user acceptance methods showed that the system functions effectively and delivers accurate and informative diagnostic results. The system achieved an accuracy rate of 100% when tested on validated expert data. Therefore, this system can serve as an effective tool for cat owners to quickly and independently gain initial insights into their cat’s skin health before consulting a veterinarian.