Education is one field in many countries that has been supporting to help the people growth. In the knowledge manner, education is importance activity to endorse and increase the people in economic and development culture. In the sub town, the problem of government policies is choosing a priority where the sub town that has a high priority and essential to realize their development in education. The purpose of the research is applying K-Means Clustering algorithm and cluster the education data, such as population, class room, and teacher. This process has been useful to cluster the data in education field. The high priority in the system, it can be supported by government firstly. In clustering process, we have been using 35 data that has been distributed in central java. The algorithm that has processing conducted by cluster technic that includes three terms such as weak frequency (cluster 1), middle frequency (cluster 2), and tight frequency (cluster 3). So, we have been setting for K-Means value is three clusters. The conclusion of the research is the sub town that has a high priority would be endorsed in education development firstly is around Magelang with 11 districts