Sistem Pakar Diagnosis Dini Penyakit Rabies pada Anjing Menggunakan Metode Forward Chaining & Certainty Factor di Puskesmas Hewan Kecamatan Selat

Abstract

Rabies is a zoonotic disease that remains a significant public health concern in Bali Province, one of the rabies endemic regions in Indonesia. The increasing number of rabies cases reported each year indicates that controlling the disease continues to be a major challenge, particularly due to the high population of dogs, which serve as the primary carriers and transmitters of the virus. Rabies virus infection can lead to severe health consequences if not addressed promptly and appropriately. Delays in recognizing rabies symptoms in pets may increase the risk of disease transmission to other animals as well as humans. This study aims to design an expert system that can be utilized as a decision-support tool for the early diagnosis of rabies in dogs. The system is designed to emulate the reasoning process of a veterinarian in making diagnostic decisions based on observed symptoms. The diagnostic process combines the Forward Chaining method, which is used to trace facts and symptoms provided by users, with the Certainty Factor method, which is applied to handle uncertainty by calculating confidence levels based on expert-assigned weights and the user's degree of confidence in the selected symptoms. The system was implemented using the Laravel framework, with MySQL serving as the database management system. System evaluation was conducted using 20 medical records as testing samples. The results demonstrated an accuracy rate of 90%, indicating that the expert system is capable of identifying potential types of rabies based on the symptoms entered by users. Therefore, the developed expert system can serve as a supporting tool for the early diagnosis of rabies in dogs in a fast, accurate, and knowledge-based manner.