<![CDATA[This study examines the effect of temperature, roasting time, and coffee bean weight on the maturity level of roasted coffee beans, utilizing fuzzy logic to model and predict optimal roast outcomes. Coffee bean roasting level, a critical factor in determining flavor, is assessed using Mamdani-type fuzzy logic, which takes three input parameters—temperature, time, and weight—divided into ranges for specific roast outcomes. Case study parameters, including a coffee bean weight of 450 grams, roasting time of 39 minutes, and temperature of 130°C, were analyzed to classify the roast maturity. The fuzzy logic output indicates that this specific case falls within the medium roast level by the similarity of centroid between moment calculation and matlab calculation is 10,7, demonstrating the model's capability to provide precise roast classifications. This structured approach to evaluating coffee roasting parameters contributes to enhancing consistency and quality in the coffee industry, highlighting the potential of fuzzy logic for robust decision support in coffee quality control.]]>
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