<![CDATA[a manual system, so it often causes subjectivity and is not accurate in describing the performance conditions of employees. With a large number of employees, a system is needed that is able to provide assessments quickly, accurately, and objectively based on several assessment criteria. The research model conducted is a quantitative approach with the Fuzzy Mamdani algorithm-based data mining method using the CRISP-DM framework. The study was conducted on 45 employees based on five input variables, namely discipline, productivity, initiative, rigor, and responsibility. The evaluation process is carried out through the stages of data understanding, data preparation, modeling and evaluation using the Fuzzy Mamdani method. From the results of the study using the Fuzzy Mamdani method, the results of performance evaluation were obtained which were divided into three categories, namely 10 employees with the good category, 34 employees with the adequate category, and 1 employee with the poor category. These results show that the Fuzzy Mamdani method is able to provide a more flexible and objective assessment than the conventional method, so that it can be used as a decision support system in evaluating employee performance. ]]>
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