<![CDATA[The low public awareness regarding early symptoms of Diabetes Mellitus at Nediva Husada Pagelaran Clinic poses a significant challenge to early detection and disease prevention efforts. Late detection often worsens the patient's condition due to untimely treatment. This study aims to develop a web-based Decision Support System (DSS) as an early screening tool for diabetes risk using the Certainty Factor (CF) method. This method was selected for its ability to handle uncertainty in symptom data experienced by patients. The research began with data collection through observation and expert interviews to determine symptom weights. System development utilized the Rapid Application Development (RAD) method, encompassing planning, design, and implementation phases. Test results indicate that the system is capable of providing early detection recommendations that are mathematically consistent with CF calculations when compared to manual calculations. Furthermore, black box testing demonstrated that all system functions operated correctly, achieving a 100% success rate in accordance with the defined functional requirements. It is important to note that this system serves as an initial screening tool, not a medical diagnosis. This system is expected to assist the community in performing self-detection before undergoing further medical examination, thereby minimizing the risk of complications.]]>
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