Employee's Performance Development via Fuzzy Logic Technique and Expert System

Human resources work performance quality is one of the strengths to maintain the success and sustainability. The efficient work performance enables enormous opportunities for local and global competitions in the field. Evaluating, monitoring, and motivating employees' efficiency are few factors that improve an organizational performance. However, most of these factors rely on manual and partially computing-based systems and need to upgrade with evolving technologies. Artificial intelligence is vital one in providing intelligent solutions for most of the human problems. This study aims to propose an expert system for evaluating employee performance based on certain predefined factors which are used at King Khalid University. The proposed system is designed using fuzzy logic through Fuzzy-CLIPS performance. “IF-Then” rules are formulated to CRISP inputs following the Ricard triple scale. Fuzzy sets are created and the moment-defuzzy functions are chosen for the Defuzification process and outputs as CRISP output values. The system is expected to simulate the employees' behavior, evaluates performance, and provides valuable recommendations to decision making authorities. The system includes the factors, such as a sense of responsibility, cooperation, communication, achieving results, development, functional connection, and leadership. System test results show that the proposed expert system performs efficiently following ground rules, gives expert opinions, and is deemed capable of simulating a human expert.