Data Mining Implementation in Admission of New Students Using Zone Systems

Abstract

Every aspect of education that is now in place has to be continuously improved by the government. The Admissions Process for New Students (PPDB) in schools that have a zoning system in place is examined in this study. The primary goal of the study is to use the clustering approach to calculate the distance between students and schools. Analyzing, gathering, processing, and evaluating data are all steps in the research methodology. The study's findings demonstrate how the zoning system has a big impact on school enrollment trends. These results highlight how crucial it is to keep the PPDB's zoning system under constant review in order to provide equitable access to education for all pupils without sacrificing educational quality. The investigation ultimately discovered clustering in the distance, classified as the closest and farthest radius, between the student's home and the school. as well as the significance of a more comprehensive study.