Prediction of Student Scholarship Recipients Using the K-Means Algorithm and C4.5

Abstract

The government has a program called "KIP Lectures" to assist students in financing education. Where PTS makes the selection manually, with the Data Mining technique, a process will be carried out to speed up the manual process. This research will apply the clustering method with the K-Means algorithm and the classification method with the C4.5 algorithm, as well as a test using the RapidMiner application, which utilizes applicant data in 2022 with a total of 1298 participants. The test results found that 327 participants were in the highest cluster, "cluster_0", then the results of the c4.5 algorithm test obtained a decision tree if the participant has a KIP Card and the value obtained from the "Total Income" Criterion is more than 70 points, then the participant concerned is entitled to scholarship where 317 participants meet the criteria, and the university only has to choose participants from the results obtained in accordance with a predetermined quota.