Fuzzy Subtractive C-Means for Teacher Distribution Analysis Nirwana, Arie Vatresia, Asahar Johar
1Science Education, Education Faculty, University of Bengkulu, Bengkulu, Indonesia
2Informatics, Engineering Faculty, University of Bengkulu, Bengkulu, Indonesia
2Information System, Engineering Faculty, University of Bengkulu, Bengkulu, Indonesia
Abstract
One of factors to maintain the quality of education is a good teacher distribution based on the school resources and requirements. The better balance of the teacher will improve the quality of management education in school. Although there is a data to record the number of teachers in the school, the adequacy value of teacher distribution over the school in Indonesia remain an open question. Here, we showed the implementation of fuzzy subtractive C-Means to see the cluster of teacher distribution over Bengkulu area. This research used new improved method of K-Means clustering that can show a better representation of teacher distribution in Bengkulu. The data used are numbers of the teachers teaching in each school, number of students, numbers of group study, number of teaching hours needed. It was implemented on to 25 secondary schools and 11 high schools over Bengkulu are to see the cluster developed in the province for 8 subjects. The research clustered the teachers on to 5 cluster with its unique characteristics to see the condition of the distribution in Bengkulu. The validation value of the system was 100% using the black box method and the clusters were validated using Silhouette with 65.6% of the highest performance.
Keywords: Fuzzy Subtractive C-Means, Teachers distribution, Bengkulu, Management Education, School
