Sistem Pendukung Keputusan Pemilihan Calon Karyawan Baru Menggunakan Metode Weight Aggregated Sum Product Assesment (WASPAS)


  • Yogi Wibisono * Mail Universitas Budi Darma, Medan, Indonesia
  • Hery Sunandar Universitas Budi Darma, Medan, Indonesia
  • Sumiaty Adelina Hutabarat Universitas Budi Darma, Medan, Indonesia
  • (*) Corresponding Author
Keywords: Decision Support System; Election; New Employees; WASPAS Method

Abstract

  1. Astra Credit Companies Medan is often abbreviated as ACC, which means that it is the largest car financing company in Indonesia, one of which is in the city of Medan, which provides financing services for the purchase of new and used cars. Problems that often occur at PT. Astra Credit Companies at the time of selecting new employees are often influenced by subjective factors where the company at the time of selecting new employees based on personal relationships only or in other words the selection of new employees is currently still random. so the results are not satisfactory. Therefore, to maximize the quality of the company will make data on the assessment criteria as a consideration in the selection of new employees. The criteria data made are Education, Psychological Test, Age, and Work Experience and Height. In this study, the author uses the Weight Aggregated Sum Product Assessment (WASPAS) method for employee selection. The WASPAS method is considered in accordance with the selection of new employees because the WASPAS method performs a ranking process based on different attributes and weights, so that the results are more optimal. determine the acceptance of new employees. Based on calculations using the WASPAS method on the selection of new employees at PT. Astra Credit decided only three people passed. selected according to the company's requirements, namely Muhammad Rasyid with a value of 0.6567, Aisya Putri with a value of 0.6513, and Elsya Putri with a value of 0.6275. The conclusion is that the three alternatives are set to be accepted as new employees at PT. Astra Credit Companies in accordance with the existing criteria.

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Published: 2022-10-31
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