<![CDATA[The process of selecting the best employees often faces various challenges that can affect the objectivity and fairness of the results. One of the main issues is the objectivity of selecting the best employees, where appraisers may have personal preferences or prejudices that influence their decisions in making the best employee selection. This study aims to apply a more objective and systematic approach in assessing employee criteria and integrate these factors into a more structured decision-making process. By using the entropy weighting method to objectively determine the weight of the criteria and TOPSIS to rank employees based on their proximity to the ideal solution, this study is expected to provide a solid foundation for more accurate and reliable decision-making in human resource management. The application of a combination of entropy weighting and TOPSIS methods in the selection of the best employees offers a comprehensive and structured approach in overcoming the complexity of human resource evaluation. The entropy weighting method is used to objectively determine the weight of the criteria based on data variation, thereby reducing subjectivity in assessment. Meanwhile, TOPSIS is used to rank employees based on their proximity to the positive ideal solution and their distance from the negative ideal solution. The combination of these two methods allows decision-makers to integrate different aspects of employee criteria. The results of the ranking of the best employees gave the results of the first best employee with a final preference score of 0.97858 obtained by Aisyah, the best second employee with a final preference score of 0.79125 obtained by Misri, and the third best employee with a final preference score of 0.69712 obtained by Rudi Setiawan.]]>
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