Perbandingan Metode TOPSIS dan WASPAS Dalam Sistem Pendukung Keputusan Pengangkatan Jabatan Manager
- Juanda Hakim Lubis Universitas Medan Area, Deli Serdang, Indonesia
-
Mesran Mesran
*
Universitas Budi Darma, Medan,
Indonesia
https://orcid.org/0000-0002-8886-2013
(*) Corresponding Author
Abstract
Performance appraisal and appointment of managerial positions are crucial aspects of modern organizational management. In dealing with the complexity of the factors that influence this decision, a decision support system (DSS) is an important tool to help make the right decision. In this study, the authors made a comparison between two popular methods in SPK, namely the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS), to support the process of appointing a manager's position. The TOPSIS method relies on the concept of geometric distances to rank alternatives based on proximity to positive and negative ideal solutions. On the other hand, the WASPAS method assigns weight to each criterion and calculates the aggregate results for each alternative, resulting in a ranking based on the highest score. This study involved a dataset containing diverse and complex performance evaluation criteria for prospective managers. The experimental results show that both methods have their own strengths and weaknesses in generating alternative rankings. The TOPSIS method provides a more stable and consistent solution in dealing with variations in sensitivity to changes in criteria weights, while the WASPAS method tends to be more adaptive to scenarios where the relative preferences between criteria differ. In the context of appointing a manager, choosing the DSS method that is appropriate to the characteristics of the organization and the preferences of decision makers is a determining factor. Both of these methods can provide valuable guidance to decision makers in selecting the most suitable candidates for managerial positions. Therefore, an in-depth understanding of the differences and practical implications of the TOPSIS and WASPAS methods is essential in the context of intelligent and efficient decision making. The results of the comparison between the TOPSIS and WASPAS methods show that the results of both have the same highest rank, namely in alternative 9 in the name of Muhammad Faisal.
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