DEVELOPMENT OF AN EXPERT SYSTEM FOR DIAGNOSING RICE PLANT DISEASES USING FORWARD CHAINING METHOD

Abstract

This study presents the development of an expert system for diagnosing rice plant diseases using the forward chaining method. Rice is the staple food for most of the Indonesian population, and plant diseases significantly reduce productivity. Farmers often face difficulties in identifying diseases due to limited agricultural knowledge and lack of experts in the field. The proposed system was designed to assist farmers in diagnosing rice diseases based on symptoms entered into the system. The forward chaining inference technique was implemented to match symptoms with disease rules in a knowledge base. The system was tested using several common rice diseases such as blast, bacterial leaf blight, tungro virus, and brown spot. Results show that the system can accurately provide disease diagnosis recommendations with clear explanation facilities. The novelty of this research lies in the application of a simple but effective reasoning method combined with a user-friendly interface for farmers. This study concludes that the system can be used as an alternative decision support tool for early disease detection in rice plants.