TY  - JOUR
AU  - Chen, Lucky Christopher 
AU  - Utama, Ditdit Nugeraha 
PY  - 2022
TI  - Decision Support Model for Determining the Best Employee using Fuzzy Logic and Simple Additive Weighting
JF  - Journal of Computer Science
VL  - 18
IS  - 6
DO  - 10.3844/jcssp.2022.530.539
UR  - https://thescipub.com/abstract/jcssp.2022.530.539
AB  - 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.