<![CDATA[Delays in the early diagnosis of rabies remains a significant issue due to the limited of public knowledge in recognizing the symptoms of the disease, resulting in delayed medical treatment. This study aims to develop a web-based expert system designed to assist in the early diagnosis of rabies in humans using the Certainty Factor (CF) method. This method is used to calculate the confidence level of the diagnosis based on the symptoms selected by the user. The system knowledge base was obtained through expert interviews and literature studies, which were represented in the form of diagnostic rules. The system is capable of providing rabies diagnosis results along with their corresponding confidence values based on the symptoms entered by users. Functional testing using the Black Box Testing method showed that all system features functioned properly. In addition, system validation was carried out by comparing the system diagnosis results with expert diagnoses through 30 testing scenarios using different symptom combinations. The test results showed 27 matching data and 3 non-matching data, resulting in a system accuracy rate of 90%. This research contributes to the implementation of the CF method in a web-based expert system to support early rabies diagnosis in a fast and measurable manner.]]>
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