This research analyzes the application of three Multi-Attribute Decision Making (MADM) methods—Simple Additive Weighting (SAW), Weighted Product (WP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)— in a Decision Support System for selecting the best employee at a company. The research variables are the criteria determined by the company's management to assess employee performance, which include performance, attendance, years of service, and attitude. This Decision Support System (DSS) implements a comparison of these three classic MADM methods to observe potential differences in the resulting rankings. The results of this study show that the application of both the SAW and WP methods produces the same ranking order, while the TOPSIS method provides a different ranking result.
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