School Clustering Using Fuzzy C Means Method
Abstract
Subang State Polytechnic is one of tertiary institution which was established in 2014. As a new tertiary institution this institution certainly competes with other tertiary institutions in obtaining prospective students. Currently, Subang State Polytechnic determines some schools to be visited for socialization activities for New Student Admissions based on the large number of students in the schools at Subang district. However, it does not prove that it has influenced the students to enroll in Subang State Polytechnic. This research highlights the issues involved in each school including the number of graduates, graduates who continue to colleges, graduates who continue to Subang State Polytechnic, average score of school’s national examination, average report card grades, number of counseling guidance teachers, number of college socialization, and the distance from the school to Subang State Polytechnic. As a result, there are 40 schools that are selected to determine as the potential schools do a socialization. The grouping schools use the Fuzzy C Means method and determe the number of groups or clusters use Modified Partition Coeffcient (MPC). The results of the MPC calculation revealed that there are 3 clusters, each cluster has a cluster center and members. In cluster I, there are 9 schools, cluster II has 16 schools, and cluster III consists of 15 schools. The results of the clustering assisted the New Student Admissions committees in determining the potential schools to do a socialization activities and it was a major step towards the success of the New Student Admissions at Subang State Polytechnic.