Analysis of combination k-means clustering and technique for order preference by similarity in recommendation of scholarship.

Scholarships are financial assistance provided by an institution/company, government, and even universities to students who meet the scholarship requirements. The many types of scholarships and different requirements make some students confused in choosing the right type of scholarship for them to be successful in getting a scholarship. This study applies data grouping techniques to determine the appropriate scholarship group. For this reason, a clustering algorithm with a partition approach was developed using the K-Means algorithm. Then, this study also conducts a decision support process with the TOPSIS algorithm to make scholarship recommendations so that users can choose scholarships from the previous process. Then, for the results of the study, a system test was carried out with scholarship recipient data which was still ongoing for 25 scholarship recipients and obtained a good system result, namely an accuracy of 88%. [ABSTRACT FROM AUTHOR]