Prediction Analysis of Kartu Jakarta Pintar (KJP) Awardees in Vocational High School XYZ Using C4.5 Algorithm

Abstract

The purpose of this paper is to analyze data and predict students who have the potential to acquire Kartu Jakarta Pintar (KJP) scholarships. KJP is a financial assistance program from the government of Special Capital Region of Jakarta granted to Jakarta citizens who are poor to allow them to receive proper education until graduating from senior high school or vocational high school. One problem arising in its implementation is the provision of KJP that is not on target, which is due to uneven distribution of information and inaccurate decision making. To overcome this problem, it is necessary to analyze the data regarding previous KJP awardees, using data mining techniques. The method applied in the current study is a decision tree with C4.5 algorithm. Decision tree is used to help simplify the decision-making process, so that decisions can interpret the solution of the problem. Thus, based on data analysis of KJP awardees, the level of accuracy will be obtained, which proves the C4.5 algorithm can be used as an alternative method in determining prospective KJP awardees.