<![CDATA[Determining the best employee is one of the essential processes in improving the quality of human resources within a company. Manual evaluation processes often lead to subjectivity, require considerable time, and may result in less accurate decision-making. This study aims to develop a Recommendation System for Determining the Best Employee using the Simple Additive Weighting (SAW) method as a decision support tool. The SAW method was selected because it is capable of evaluating multiple criteria by considering the importance weight of each criterion. The research stages include requirements identification, determination of criteria and their respective weights, employee data collection, normalization, preference value calculation, and alternative ranking. The developed system is capable of processing employee data in a computerized manner, making the evaluation process faster, more objective, and more efficient. Based on the testing results, the system successfully produced the highest preference value of 0.956, indicating that the employee was selected as the best alternative according to all predefined criteria. The findings demonstrate that the SAW method can be effectively implemented in a recommendation system for determining the best employee and can assist management in making accurate, transparent, and measurable decisions.]]>
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