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Analisis Penilaian Kinerja Karyawan Dengan Metode Simple Additive Weighting Di PT Paiho Indonesia Febriani, Ersa; Muslih, Muhamad
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.451

Abstract

An employee performance appraisal decision support system is used to evaluate the best employees. The company evaluates the performance of its employees to evaluate, motivate and verify employee performance improvements. The results of this performance can be used as a reference for superiors to carry out promotions, dismissals, transfers, and employee bonuses. The assessment in this study was carried out using five criteria, namely attendance, attitude/ethics, expertise, quantity, and quality, using the simple additive weighting (SAW) method. This study tested data from 50 respondents, and obtained 100% data accuracy from the test calculations, ie the large number of appropriate data divided by the large number of tested data multiplied by 100%.
Analisis Penilaian Kinerja Karyawan Dengan Metode Simple Additive Weighting Di PT Paiho Indonesia Febriani, Ersa; Muslih, Muhamad
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.451

Abstract

An employee performance appraisal decision support system is used to evaluate the best employees. The company evaluates the performance of its employees to evaluate, motivate and verify employee performance improvements. The results of this performance can be used as a reference for superiors to carry out promotions, dismissals, transfers, and employee bonuses. The assessment in this study was carried out using five criteria, namely attendance, attitude/ethics, expertise, quantity, and quality, using the simple additive weighting (SAW) method. This study tested data from 50 respondents, and obtained 100% data accuracy from the test calculations, ie the large number of appropriate data divided by the large number of tested data multiplied by 100%.