<![CDATA[The management of banana pest and disease outbreaks in Ngada Regency since 2022 has been hindered by farmers' lack of knowledge about early detection of symptoms and the limited availability of agricultural extension workers, which accelerates the spread and increases losses in agricultural land. This study aims to develop a web-based expert system to assist farmers in diagnosing banana pests and diseases quickly and accurately. The research methods involved data collection through field observations, interviews with farmers and agricultural experts, and literature studies from relevant references. The system design employs the waterfall development model, which includes requirements analysis, system design, implementation, and testing. The knowledge base of the system is designed using the forward chaining algorithm with 9 types of diseases and 40 symptoms. Implementation results indicate that the system was successfully tested using the black-box method with a 100% success rate, while the usability and responsiveness aspects scored 98% based on user evaluations. In conclusion, the forward chaining algorithm serves as an effective methode to support the diagnosis of banana pests and diseases and to enhance farmers' knowledge, thereby reducing losses caused by pest and disease attacks.]]>
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