Classifying High School Scholarship Recipients Using the K-Nearest Neighbor Algorithm

Abstract

YBM PLN UIWS2JB provides scholarships for high school students who cannot afford school tuition due to poverty or other economic conditions. Since the target is specific, the foundation must carefully select the recipients to ensure the scholarship is granted to those who deserve it. The predetermined criteria combined with the limited quota available become a difficulty in itself as a large number of applications are coming in. Data mining with a classification method using the K-Nearest Neighbor algorithm is believed to be one of the alternative solutions to solve this problem. This study aims to examine how this method could help in the selection process to determine who is eligible to receive the scholarship, and it also aims to evaluate the algorithm's performance with the optimal K value. The findings of this research showed that the classification method using K-Nearest Neighbor is the potential to be applied in a case such as this. The results found an accuracy of 91% in the selection process and are included in the Excellent Classification category. The optimal K value obtained is K = 5.