<![CDATA[This research is about the grouping of prospective students who will receive KIP scholarships. Data mining is a conception or design made with the aim of finding an added value contained in a database that will be able to identify a useful knowledge information. In this study, the concept of data mining was applied to assist campuses in predicting students who will get KIP scholarships by implementing the K-MeansClustering Algorithm, where the K-MeansClustering algorithm can later group each data into clusters so that data that has the same characteristics will be grouped in the same cluster and vice versa if the data has different characteristics then it is grouped into another cluster. The results of this study are 3 cluster results which will be the final result, namely data received as scholarship recipients as many as 52 data, 32 data are grouped as recipient data which will be recommended to the next stage. while the remaining 16 data are grouped as data that is not accepted]]>
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