Higher Education Clustering in Indonesia by using k-means and Geographical Similarity Methods

Abstract

: Diverse quality and equality in higher education has been concerned by government of Indonesia. It is because these aspects have positive correlation with the country development and competitiveness. Meanwhile, improvement policy should be supported by better perspective and mapping about the condition of the higher education in this country. Although, ministry of research and higher education of Indonesia has published statistical data, the analysis of it is veiy limited. Based on this problem, we use clustering method to analyze this higher education statistic data, so that, new perspective and understanding can be explored. In this research, we use two computational methods: k-means and geographical similarity, so that, the analysis can be enriched. In this research, we also compare the condition in private institution and public institution. Result shows that in some aspects, there is disparity between private institution and public institution. Meanwhile in some aspect, there is disparity between Java Region and other regions in Indonesia