TY  - JOUR
AU  - Aljofarinski, Hiromi Jorge Akbar 
AU  - Utama, Ditdit Nugeraha 
PY  - 2022
TI  - Decision Support Model to Determine the Best Employees (Mechanic) using Fuzzy Logic and Profile Matching
JF  - Journal of Computer Science
VL  - 18
IS  - 6
DO  - 10.3844/jcssp.2022.540.554
UR  - https://thescipub.com/abstract/jcssp.2022.540.554
AB  - In a company, verifying the best employees is practically very essential. Knowing the best employees or understanding each employee's performance can be an advantage for the company to evaluate the whole company's performance and improve the lack. Determining the best employees is also necessary for giving appreciation to employees and is expected to be able to expand the performance and morale of employees. This study aims to build a Decision Support Model (DSM) to determine the best employee using a combination of fuzzy logic and profile matching methods. In developing the model, there are twelve selected parameters considered; i.e., performance problem diagnosis, problem-solving, preventive action, concept, time management, disciplinary, work management, efficiency, education, support skills, and business workflow. Finally, the model has been methodologically constructed. It is operated in determining the best employee (especially for mechanic staff in workshop) thru evaluating all employees' performance.