<p><em>Recruitment of students in private universities has its challenges for the campus. The grouping of students based on school origin, city, and province is one method of recruiting new students; data mining in the grouping can be done using the K-Means Clustering algorithm. Implementing the K-Means Clustering Algorithm is relatively easy. It has fast computing, so it can be used to analyze college student profile data to help increase the selection of new students in the following year. In the data that has been grouped with K-Means Clustering, there are 3 clusters; cluster 1 (cluster_0) is domiciled in cities in Central Kalimantan Province. Cluster 2 (cluster_1) is dominated by students from various cities in South Kalimantan Province, and cluster 3 (cluster_2 ) is dominated by students from Banjarmasin, South Kalimantan province. Student selection strategy could be even better based on analysis using K-Means Clustering.</em></p>