MEASURING THE PERFORMANCE OF EMPLOYEES WITH FUZZY LOGIC

Abstract

Employees are the most valuable assets for an organization today. Many factors such as educational background, job skills and abilities should be considered when selecting and evaluating employees. Any institution or organization aims to improve the performance of its employees, to achieve its business goals and to select the right employee when recruiting. Fuzzy logic, which is one of the artificial intelligence techniques, is a decision-making method that enables the strengthening and improvement of human resources and finding the best solution to uncertain problems. In order to select the right employee by using fuzzy logic, many performance evaluation criteria are considered, and the candidates are scored with a decision-making mechanism. This study's objective is to use fuzzy set theory, the Mamdani method, to measure and assess performance during the personnel evaluation and selection process in order to produce the most accurate conclusions for the organization. Fuzzy logic clusters with multiple parameters to provide answers to uncertainties will be used in this study. The performance of current employees is measured using the Mamdani method and training help and awards are given in accordance. According to the outcome as measured, improvements should be made. Candidates are ranked according to their scores, and it is aimed to determine the best one as a result. In order to improve the performance of existing employees with a fuzzy logic decision-making mechanism, first of all, it should be determined which rating criteria the employees lack. Afterward, it is expected that the person will improve himself/herself in this field by providing training according to the needs. If the person is still not at the desired level, the job can be terminated.