Expert System for Diagnosing Banana Plant Diseases Using the Forward Chaining Method: A Case Study in Mauliru Village

Abstract

Bananas (Musa spp.) are a horticultural crop that plays a significant role in the Indonesian economy, particularly for farmers in Mauliru Village. However, the main obstacle faced by some farmers is disease attack such as affected by diseases such as blood disease, fusarium wilt, and cercospora leaf spot. These issues are further exacerbated by limited farmer knowledge and the lack of agricultural experts available to provide assistance. To address this problem, this study proposes the development of a web-based expert system to assist farmers in diagnosing banana plant diseases. The system employs the Forward Chaining method, which operates based on symptoms entered by the user, and integrates the Certainty Factor (CF) method to provide confidence levels for diagnostic results. This system offers information on the identified disease and recommended treatment solutions, enabling farmers to respond more quickly and effectively. Testing results indicate an accuracy rate of 80%, demonstrating that the system is a viable tool for identifying banana plant diseases, especially in regions with limited access to expert support.