Implementation of Fuzzy C-Means and Topsis in College Rankings

Abstract

Prior to now, the ranking of higher education institutions, particularly those at the Regional II Palembang Higher Education Service Institution, was based on one component of the work unit's criteria. This makes the university ranking results superior on one criterion but inferior on another. The number of instructors and the number of students at 100 universities in the South Sumatra region were split into two groups based on the outcome of the fuzzy c means algorithm grouping and regional criteria and calculated based on the resulting mean value. The grouping results using a topsis algorithm decision-making system with a weight determined by the number of lecturers with functional positions, college accreditation, number of certified lecturers, and percentage level of higher education database reports are used as a reference to rank universities. Based on the mean value of the fuzzy c means algorithm and the grouping results, seven colleges were chosen. Using the topsis method's way of making decisions, the final score for the highest-ranked college is 0.850.

Keywords

• ranking
• higher education
• clustering
• decision making