<![CDATA[Type 2 Diabetes Mellitus is a metabolic disease that requires precise regulation of daily calorie intake to maintain stable blood sugar levels. Determining calorie requirements is not simple because it must take into account factors such as age, gender, body mass index (BMI), and physical activity level. This study aims to develop a Mamdani fuzzy logic-based expert system to provide recommendations for daily calorie requirements for people with type 2 diabetes. The system process is carried out through the stages of fuzzification, inference, aggregation, and defuzzification using the centroid method. Testing was conducted using 20 type 2 diabetes patient data with input variables of age, height, weight, gender, and physical activity. The testing methods used were accuracy and black-box. Accuracy testing was performed by comparing the system's results with manual calculations based on medical standards, while black-box testing ensured that the system functioned as designed. The results showed that the system had an accuracy rate of 80%, making it sufficiently valid and usable as a tool for recommending daily calorie intake to support diet management for type 2 diabetes patients.]]>
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