<![CDATA[Dengue Hemorrhagic Fever (DHF) is a significant health issue in Indonesia, particularly in the city of Bandung. This condition necessitates prompt intervention and precise diagnosis to ensure patients receive timely and suitable treatment. The insufficient number of medical workers, particularly physicians, in various clinics, including the Healthy Life Clinic, constitutes a significant impediment to the early diagnosis of DHF. This project aims to develop and apply an expert system for diagnosing DHF using the forward chaining method. This approach operates by tracing data from user-inputted facts or symptoms to derive diagnostic conclusions. This expert system is designed to replicate a physician's cognitive process in evaluating symptoms and providing guidance for the early diagnosis of DHF. The study's results indicated that the created method achieved a diagnosis with high accuracy and strong consistency with the test data. Furthermore, the system demonstrated superior performance in terms of response speed and user-friendliness. Validation tests and simulations based on actual cases managed by the clinic were conducted for testing purposes. The system's efficacy is significantly contingent upon the quality and comprehensiveness of the data input by the user. A further deficiency identified was the need for regular updates to the knowledge base to ensure the system's relevance to the latest advancements in the medical field. Despite several constraints, this expert system has demonstrated its efficacy as a practical and effective diagnostic tool, particularly for clinics with limited medical staff. The incorporation of artificial intelligence through the forward chaining method is anticipated to serve as a strategic solution for enhancing the quality of health services and expediting the management of DHF cases at primary healthcare facilities.]]>
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