EXPERT SYSTEM FOR DIAGNOSING DISEASES IN CUCUMBER PLANTS USING FORWARD CHAINING METHOD - ilham assidiq; Hetty Rohayani; Hendra Kurniawan (International Journal of Innovation Research in Education, Technology and Management, 2026)
The purpose of this research is to develop an expert system to diagnose plant diseases in cucumber using the forward chaining method. The agricultural sector, particularly vegetable cultivation, faces great challenges due to the spread of diseases that reduce productivity and economic value. Expert systems mimic human expertise to accurately diagnose diseases and provide practical solutions by providing effective recommendations. The forward chain, rule-based reasoning approach, ensures systematic analysis to derive conclusions from known facts, thereby improving diagnostic accuracy. The focus of this research is to identify common diseases in cucumber plants and encode the expertise into a functional system. The development of the system involved gathering knowledge from agricultural experts, creating rules, and implementing them in a user-friendly interface. Preliminary results show the high accuracy and potential of the system to help farmers quickly diagnose diseases and take preventive measures. This paper contributes to sustainable agriculture by integrating an expert system to effectively address plant health issues. Future enhancements may include real-time monitoring and integration with IoT devices.