<![CDATA[The outsourcing industry in this study has 53 employees internally, so to support the progress of the company, it is necessary to thank employees who have given good dedication. In giving appreciation, there must be a selection process for the best employees. However, the difficulties of the manual selection process and the subjectivity of department heads made the process longer, with some employees complaining about decisions that were not on target. In this problem, researchers try to change the manual system and subjectivity by implementing a decision support system using a simple additive weighting method. The general description of the Simple Additive Weighting (SAW) method is to find the weighted sum of the performance ratings of each alternative for all attributes. The criteria and weights that determine the best employees in this outsourcing industry are presence (20%), discipline (10%), thoroughness (10%), leadership (30%), relationships (20%) and tenure (10%). Higher ratings and scores will indicate that the alternative is preferred. The alternatives that will be used in this study are 53. In the final results of the SAW calculation there are The 10 best alternative (employee) recommendations are A23 with a score of 0.9167, A4 with a score of 0.9167, A15 with a score of 0.9167, A32 with a score of 0.9167, A34 with a score of 0.8917, A24 with a score of 0.8917, A19 with a score of 0.8917, A18 with a score of 0.8750, A28 with a score of 0.8417, A29 with a score of 0.8417. The final result of the SAW calculation shows that the weighting of the criteria affects ranking]]>
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