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

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.

The Decision-Support Modeling with Fuzzy Analytic Hierarchy Process (AHP) to Determine the Career Path for Bachelor Informatics Students

“…The inception of the Decision Support Model may be traced back to 1970, when it was initially introduced by Scott Morton. The problem-solving process is facilitated by the utilization of specific data and models in this system [38]. Decision support models may not always yield completely accurate outcomes due to their reliance on a technology that emulates human decision-making processes [39].…”

Problem Solving and Decision-Making Skills for ESD: A Bibliometric Analysis

“…This is because the interaction among various stakeholders and knowledge exchange can enhance the processes of making appropriate decisions (Cai et al, 2023). According to a study in various fields, the outcomes obtained were significantly related to decision-making skills in learning mathematics (Pertl, Zamarian and Delazer, 2017), physics (Silvianty, Suhandi and Setiawan, 2019), chemistry (Gao, 2015;Lieber et al, 2022;Wilson and Wilson, 2017), medicine (Delavari et al, 2022), computers (Carlsson, 2019;Chen and Utama, 2022;Méndez et al, 2020), engineering (Fruchter, Katz and Grey, 2018), business (De Villiers, Hankin and Woodside, 2016), and nursing Macduff, Stephen and Taylo, 2016;Saab et al, 2021). Kwok and Hodgson (2017) also stated that decisionmaking model consisted of six steps, namely identifying problems, generating, evaluating, and selecting alternatives, as well as implementing and assessing decisions.…”