Application of K-Means Clustering Algorithm in Determining Prospective Students Receiving Foundation Scholarship
Sabrina Aulia Rahmah, Jovi Antares · 2021
Dharmawangsa Educational Foundation provides financial assistance every new academic year to the new students who own great academic abilities, but have the poor economic background to continue studying at the college. In the distribution of the scholarship, the foundation certainly needs to conduct the selection of new students’ data correctly to get the right grantee. So far, the steps taken to select the grantee are carried out manually, namely checking and selecting one by the students’ data. Furthermore, the amounts of data that need to be selected one by one take a long time and the accuracy level of assessment are not necessarily optimal too. The study aimed to develop an application system that could improve the quality of awarding scholarships to be more objective in accordance with a grouping of each student’s criteria, so the foundation got the right grantee. The method used was the K-Means Clustering algorithm. It could form a cluster in determining the level of the data processing result. In addition, the cluster used was by the predetermined criteria, including the value of the Final School Examination, the report card value, house status, the condition of the house, and the parents’ income. The next step was to divide the information into clusters, so the information with the same character was grouped into the same cluster. The cluster was divided into three groups, namely accepted, considered, and rejected. The data used were 80 students. The result of the calculation carried out was 16.3% accepted, 61.3% considered, and 22.5% rejected.