Research Article Open Access

Decision Support Model for Determining the Best Employee using Fuzzy Logic and Simple Additive Weighting

Lucky Christopher Chen1 and Ditdit Nugeraha Utama1
  • 1 Computer Science Department, Bina Nusantara University, Jakarta, Indonesia

Abstract

Specifically, for an information technology company, identifying the best employees (the best programmers) is valuable. The election is intended to improve the performance of the company's programmers. The company's performance will improve as programmers' performance improves. This study attempts to develop a Decision Support Model (DSM) to identify the best employees (i.e., programmers) in the firm. The model considered nine parameters (technical skills, problem-solving, communication skills, teamwork, discipline, work progress, time management, formal education, and informal education) by integrating the Fuzzy Logic (FL) with the Simple Additive Weighting method (SAW). This model is finally able to be benefitted by information and technology firms. This can eventually be used to assess and view employee evaluations, making it simpler for businesses to make key decisions (e.g., granting incentives, salary raises, or promotions). The model is based on data collected from ten company programmers (where six of them are real data). The model concludes that programmer 2 is the best employee in the firm, with a total score of 97.94, based on the suggestions from the constructed DSM.

Journal of Computer Science
Volume 18 No. 6, 2022, 530-539

DOI: https://doi.org/10.3844/jcssp.2022.530.539

Submitted On: 15 November 2021 Published On: 24 June 2022

How to Cite: Chen, L. C. & Utama, D. N. (2022). Decision Support Model for Determining the Best Employee using Fuzzy Logic and Simple Additive Weighting. Journal of Computer Science, 18(6), 530-539. https://doi.org/10.3844/jcssp.2022.530.539

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Keywords

  • Decision Support Model
  • Fuzzy Logic
  • Simple Additive Weighting
  • Best Employee
  • Programmer