Penentuan Kenaikan Jabatan Menggunakan Pembobotan Metode AHP dan Didukung Metode Complex Proportional Assessment

  • Ulfy A
  • Devi P
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Abstract

The internal state of the industry related to the human energy sources owned by the industry requires something that requires a management system that can support the selection of competent human energy sources in their field. The increase in problems is very meaningful for every industry because it involves the continuation of the growth of the industry. On the issue of promotion, managers must pay attention to many things about applicable problems, not subjective. Problems that often occur in the process of promotion of employees include the subjectivity of decision making, the presence of most employees who have far different abilities. Therefore we need a decision support system that can assist in determining effective position assignments and searching for the highest value using the COPRAS method. This decision support system uses the Analytical Hierarchy Process (AHP) method and (COPRAS) Complex Proportional Assessment where this method can be used to overcome complexity because there are many criteria that must be considered in promotions such as work quality, work experience, employee skills, tardiness, absenteeism. , teamwork, responsibility, and the final diploma. The data used is the assessment in 2020 at PT. Ark Setia has as many as 13 employee data. Testing the system was tried with one trial, namely making a start with Microsoft Office Excel. The results of the experiment using Microsoft Office Excel can be adjusted to the data that has been calculated using the AHP weighting method with the support of the COPRAS method, the highest value obtained from this calculation is 100.00 and obtained 4 appropriate results and fit to get the promotion.

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APA

Ulfy, A. W. N., & Devi, P. A. R. (2022). Penentuan Kenaikan Jabatan Menggunakan Pembobotan Metode AHP dan Didukung Metode Complex Proportional Assessment. Jurnal Sistem Komputer Dan Informatika (JSON), 3(3), 232. https://doi.org/10.30865/json.v3i3.3867

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