<![CDATA[Diabetes Mellitus (DM) is a chronic disease that can lead to serious complications if not detected and treated early. According to data from WHO and the Indonesian Ministry of Health, the prevalence of DM continues to rise each year, highlighting the need for a diagnostic support system that is both fast and accurate. This study aims to develop an expert system capable of predicting Diabetes Mellitus using the Case Based Reasoning (CBR) method. CBR is applied because it solves new problems by comparing them to previous cases based on the similarity of symptoms. The system incorporates 20 symptoms classified into two types of DM: type 1 and type 2. The prediction process follows the four main stages of CBR: retrieve, reuse, revise, and retain. Test results show that the system can predict the disease with an accuracy rate of over 90%, and user feedback through Blackbox Testing and User Acceptance Testing (UAT) confirms its usability. This expert system is expected to serve as an initial consultation tool to help users obtain early information related to potential DM quickly, easily, and efficiently.]]>
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