Designing a Decision Support System for the Best Employee Selection Using AHP Method Case Study PT. Z Bali

  • I Gusti Ngurah Wira Partha Department of Electrical and Computer Engineering, Udayana University
  • Philipus Novenando Mamang Weking Department of Electrical and Computer Engineering, Udayana University
  • Yanu Prapto Sudarmojo Department of Electrical and Computer Engineering, Udayana University

Abstract

The chairman and owner of PT. Z Bali considers the employees who work in his company to be very important for the continuity of the industry in his company, so he is very concerned about what the employees need. His attention to the needs of his employees is realized by giving bonuses to employees who have the best performance in the company. Periodically he assigns tasks to the Human Resources Department (HRD) in his company to process the best employee selection or employees who have good quality work.


But the best employee selection process at PT. Z Bali is still done manually and only based on the subjectivity of the HRD, this led to the HRD has trouble making decisions, so sometimes there is an employee who obtained the title of the best people by just looking at the first criteria, but these employees have not been certainly excelled on some other criteria.


Therefore, the purpose of this research is to Designing a Decision Support System for the Best Employee Selection Using AHP Method Case Study PT. Z Bali to be able to help the difficulties that are being faced by the Human Resources Department (HRD) at PT. Z Bali.

Downloads

Download data is not yet available.
Published
2019-01-15
How to Cite
WIRA PARTHA, I Gusti Ngurah; MAMANG WEKING, Philipus Novenando; SUDARMOJO, Yanu Prapto. Designing a Decision Support System for the Best Employee Selection Using AHP Method Case Study PT. Z Bali. International Journal of Engineering and Emerging Technology, [S.l.], v. 3, n. 2, p. 51--66, jan. 2019. ISSN 2579-5988. Available at: <https://ojs.unud.ac.id/index.php/ijeet/article/view/45605>. Date accessed: 22 nov. 2024.