Schizophrenia is a serious mental disorder with a high prevalence, especially in developing countries. Many patients do not receive adequate treatment due to a lack of information and reluctance to consult with psychiatrists. This study aims to develop a web-based expert system to assist in the early diagnosis of schizophrenia based on the symptoms experienced by users. The system applies the Certainty Factor (CF) method, which is capable of handling uncertainty in medical decision-making. Symptom data and schizophrenia types were obtained from medical documentation and direct interviews with a psychiatrist at RSUD Banyumas. The system was also validated by a psychiatrist to ensure the accuracy of its diagnostic output compared to actual medical diagnoses. It is designed to be easily accessible via the web, especially for communities in remote areas, with a user-friendly interface. Functional testing using the Black Box method showed that all system features operated correctly (100% functionality). Diagnostic validation by a psychiatrist revealed a system accuracy rate of 9o%, indicating that the developed expert system can provide early schizophrenia diagnoses with a high level of confidence, close to professional assessments. This system is expected to serve as an effective early detection tool, raise public awareness, and accelerate treatment for individuals with schizophrenia.
Keywords: Expert System, Schizophrenia, Certainty Factor, Diagnosis, Website