Klasterisasi kinerja karyawan menggunakan algoritma fuzzy c-means

  • Martin Martin
  • Yessica Nataliani Fakultas Teknologi Informasi Universitas Kristen Satya Wacana
Keywords: employees' performance, clustering, fuzzy c-means

Abstract

Reward and punishment are needed for assessting employees’ performace. Employee grouping based on their performance is one of several ways to enhance employees’ performance. This research discusses about grouping employess based on their performance using Fuzzy C-Means. Result from assessment comes from the total of each criteria that contains of presence, discipline, and task duration. Three groups of employees are formed, which are good, moderate, and bad. From 13 employees, 10 of them are in the good criteria, one is in moderate criteria, and two are in the bad one. We also use different values of fuzzy exponent to get the clustering results. The values 1.5 and 2 of fuzzy exponents give the same clustering results with the result from manager. Therefore, grouping with FCM could be used to cluster employees based on their performance.

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References

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Published
2021-02-23
How to Cite
Martin, M., & Nataliani, Y. (2021). Klasterisasi kinerja karyawan menggunakan algoritma fuzzy c-means. AITI, 17(2), 118-129. https://doi.org/10.24246/aiti.v17i2.118-129
Section
Articles