Abstract: Education is a key indicator to measure the development of a nation and the quality of its human resources. Indonesia has a vast number of school components which become a challenge for the government on how to define the appropriate policies to improve the equal educational opportunities throughout the country. The level of educational development can be quantified by education index involving a number of parameters. The most common analysis of these parameters is primarily based on the statistical distribution of data. However, this current analysis has some limitations to extract the keys information that are necessary for the policy makers to recognize the educational needs that could be differ in each region. This study aims to define groups of province that have similar profiles of educational development. Research was done by clustering the education index data set which consist of 33 provinces and 15 parameters. The clustering method was based on a fuzzy clustering algorithm which was able to provide the uniformity of each generated cluster. For determining the optimum number of clusters it was based on a cluster validity measurement, i.e., Xie and Beni Index. Meanwhile for interpreting the clustering results it was based on student t-test since it involved the data comparison to the national education standards. This research showed that fuzzy clustering can be utilized to identify the cluster of provinces based on their level of achievement in education and provide some insights that might be used by the policy makers in determining the educational development priorities.