<![CDATA[Porang (Amorphophallus muelleri Blume) is a leading commodity with high export value in Indonesia. However, diseases caused by Fusarium sp. fungal infections have become a major obstacle that can lead to crop failure if not detected and treated early. Limited knowledge of farmers in identifying disease symptoms and restricted access to agricultural experts highlight the need for a technological solution that enables independent diagnosis. This study aims to develop a web-based expert system capable of diagnosing Fusarium diseases in porang plants using the Forward Chaining method. The Forward Chaining method operates in a data-driven manner by matching symptom facts inputted by users against a rule base compiled from expert knowledge. The system's knowledge base consists of 6 types of Fusarium diseases and 22 clinical symptom indicators obtained through expert interviews, which are represented in 6 production rules (IF-THEN rules). The results showed that the developed expert system is capable of diagnosing Fusarium diseases in porang plants in real-time based on selected symptom inputs, while also displaying the disease name along with recommended treatment solutions. This system is expected to assist farmers in the early detection of Fusarium diseases independently, quickly, and accurately without directly relying on agricultural experts. System testing using the black box testing method demonstrates that all system functions perform as expected, ranging from the authentication process and data management to the disease diagnosis process.]]>
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