PENENTUAN KARYAWAN TERBAIK DENGAN METODE TOPSIS PADA PT REGENCY MOTOR

Authors

  • Agus Salim Universitas Bina Sarana Informatika
  • Baginda Oloan Lubis Universitas Bina Sarana Informatika
  • Ali Haidir Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.33020/saintekom.v12i1.203

Keywords:

DSS, best employes, TOPSIS

Abstract

In carrying out its activities, PT. Regency Motor is assisted by employees who have a good work ethic. PT. Regency Motor selected the best employees who would later be given prizes as a result of the employee's hard work. This selection process often experiences several problems such as the calculation of employee criterion values that often experience similarities between one another. The best employee selection process involves all employees working at PT. Regency Motor. This process has several assessment stages which can take a long time in calculating the value of each employee. In these processes it is not uncommon for errors to occur in both the input of employee values and in the process of calculating those values. Therefore in this study the author tries to try to help the company to determine the best employees by using the Technique for Order Reference by Similarity to Ideal Solution (TOPSIS) method more effectively, because the TOPSIS method is one of the best alternatives that is able to produce employee data with using six criteria, namely discipline, loyalty, attitude, attendance, expertise and years of service, the final calculation result is obtained to determine the best employee obtained with the prefence value at the highest value, Alex Ryan with a value of 0.7592812

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References

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Published

02-03-2022

How to Cite

Salim, Agus, Baginda Oloan Lubis, and Ali Haidir. 2022. “PENENTUAN KARYAWAN TERBAIK DENGAN METODE TOPSIS PADA PT REGENCY MOTOR”. Jurnal Saintekom : Sains, Teknologi, Komputer Dan Manajemen 12 (1):92-102. https://doi.org/10.33020/saintekom.v12i1.203.

Issue

Vol. 12 No. 1 (2022): March 2022

Section

Articles

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Copyright (c) 2022 Agus Salim, Baginda Oloan Lubis, Ali Haidir

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