Application of Case Based Reasoning in a Website-based Expert System for Diagnosing Diseases in Catfish

Abstract

Diseases in catfish often become a significant problem in fish farming, which can cause major losses for farmers. To overcome this problem, a system is needed that can help diagnose diseases in catfish accurately and quickly. This research aims to develop a website-based expert system that uses the Case Based Reasoning (CBR) method to diagnose diseases in catfish. The CBR method allows the system to identify disease by comparing the symptoms experienced by catfish with data on previous cases that already exist in the knowledge base. This system consists of several main components, namely input data on catfish symptoms, case matching process, and presentation of disease diagnoses and solutions. System testing was carried out using symptom data collected from various cases of catfish disease that occurred in the field. The results of this research show that the CBR-based expert system is able to provide diagnoses that are appropriate to existing cases, and can be a useful tool for catfish farmers in detecting disease early and providing appropriate treatment. This system can be accessed online, making it easy for users to access information anytime and anywhere.