Penerapan Algoritma Simple Additive Weighting untuk Penentuan Karyawan Terbaik

Authors

  • Suprihono Suprihono Universitas Budi Luhur
  • Siswanto Siswanto Universitas Budi Luhur

Keywords:

SAW Algorithm, Best Employees, Naïve Bayes

Abstract

PT Elnusa Petrofin (EPN) provides the best contribution to employees, this award is given in the hope of motivating all employees to work well. PT Elnusa Petrofin (EPN) conducted the process of selecting the best employees, so this will of course require a long time and produce less than the maximum. Sometimes mistakes are made by the leader in relation to the best employees, see the conflict that occurs at PT Elnusa Petrofin (EPN) then an algorithm is requested to help the best employee leaders use the Simple Additive Addition Algorithm (SAW) as a method used to find alternative Simple Algorithms This Additive Weighting (SAW) can determine the best association seen from the ranking system at PT Elnusa Petrofin and the results of the ranking process with Simple Additive Weighting obtain an average result of Simple Additive Weighting (SAW) of 4.8 with a standard deviation of 3.982 and a classification process with Naïve Bayes produces an accuracy of 73.33% and an error of 26.67%, with an error value on the results of the allocations needed to predict the best employee performance.

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Published

2019-10-26

How to Cite

Suprihono, S., & Siswanto, S. (2019). Penerapan Algoritma Simple Additive Weighting untuk Penentuan Karyawan Terbaik. Prosiding SISFOTEK, 3(1), 60 - 66. Retrieved from http://seminar.iaii.or.id/index.php/SISFOTEK/article/view/104

Issue

Section

2. Rekayasa Sistem Informasi