An Decision Making of Lecturer Assessment Model Using Combining Profile Matching and Fuzzy Logic Approach

Abstract

Lecturer performance appraisal plays a role in improving the quality of education in higher education. However, the performance appraisal process often experiences obstacles related to subjectivity and uncertainty in assessing various aspects of lecturer performance. This research applies a lecturer assessment decision-making model by combining Profile Matching and Fuzzy Logic methods to create a more objective and comprehensive system. The system uses six main criteria with five alternatives for selection, including teaching quality, research and publication, and community service, which are measured based on the fit between the ideal profile and the actual performance of the lecturer. The calculation results show that the weight value of the core factor and secondary factor greatly affects the ranking results, the final results show the value of alternatives on each criterion, the value of alternatives A1, A4 and A5 has a large value on criteria C1, C2 and C3. So that if the value of the core factor weight is greater on the C1, C2, C3 criteria, it tends to make alternatives that have a large value on the C1, C2 and C3 criteria superior to other alternatives