Implementation of topsis algorithm for evaluating lecturer performance

Abstract

Higher education is an education unit that able to carry out academic, professional and / or vocational programs. Lecturers are professional and scientific educators with the main task of transforming and developing, and disseminating science, technology and art through education, research and community service. The performance evaluation applies seven criterias, namely: attendance, teaching, research, dedication, loyalty, cooperation and responsibility. The problems are; the lecturers’ performance evaluation is not optimal yet because there is no specific method to implement it. Therefore, it is necessary to build a decision support system by applying the Technique For Others Reference by Similarity to Ideal Solution (TOPSIS). This system will later help us in determining the best lecturer in accordance with the regulation. The TOPSIS method uses the principle that the chosen alternative must have the longest (farthest) distance from the negative ideal solution from geometric point of view using the relative proximity of an alternative. The alternative means the lecturers’ performance with predetermined criterias. This method produces a lecturers rankings based on the best performance on numerical scores and sorted by the greatest preference scores. The particular study used 5 lecturers as alternative to be tested. They were Lecturers 1, Lecturers 2, Lecturers 3, Lecturers 4, and Lecturers 5. The results showed that Lecturer 1 was the best lecturer with the biggest preference score of 0.612.