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All Journal Journal of Computing and Informatics Research
Ari Sulistiyawati
Universitas Teknokrat Indonesia, Bandar Lampung
Computer Science & IT

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The Combination of WENSLO and MUNRA Method in Selecting the Best Employees Based on Multiple Criteria Junhai Wang; Setiawansyah Setiawansyah; Adhie Thyo Priandika; Dedi Darwis; Ari Sulistiyawati
Journal of Computing and Informatics Research Vol 5 No 2 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v5i2.2472

Abstract

This study examines the application of a combination of the WENSLO and MUNRA methods in selecting the best employees based on various criteria to address issues of subjectivity and instability in employee rankings that often arise when data is heterogeneous and criteria are conflicting. The WENSLO method is used to assess and prioritize criteria through structured and preference-based weighting, while MUNRA plays a role in consistently normalizing data and calculating weighted scores for each alternative. The integration of these two methods allows for a more objective evaluation, reduces subjective bias, and produces stable employee rankings even in the presence of data variations or conflicting criteria. The Employee Ranking results show that the top-performing employee is Lestari with a score of 1.3092, followed by Susilo with a score of 1.3080 and Maharani with a score of 1.3003, indicating superior and relatively balanced performance. These findings confirm that the combination of WENSLO and MUNRA can produce clear, objective, and effective employee rankings, as well as provide an adaptive framework to support strategic human resource management.
Co-Authors Dedi Darwis Junhai Wang Priandika, Adhie Thyo Setiawansyah Setiawansyah