Implementation of Feature Enginering and K-Mean Clustering Model in Predictive Analysis of Improving The Quality of Junior High School Education in Bogor Regency

Abstract

In order to improve the quality of education. The government of the Republic of Indonesia has established the National Education Standard (SNP) which is the minimum criterion set by the government in the education system. SNP is a standard that must be met by every school and all stakeholders in managing and delivering education. Through data analysis using feature enginering and K-meann methods to predict the quality of junior high school education in Bogor Regency shows that the junior high school education standards in Bogor Regency are significantly influenced by the achievement value of 3 education quality standards, namely educator and education staff standards, facilities and infrastructure standards, and management standards. So that the education office of Bogor Regency needs to focus the direction of policies to improve the quality of junior high school education in indicators that affect these 3 standards. The results of the k-men clustering of school quality showed that junior high schools in Bogor Regency were divided into 2 major groups of education quality level, namely below the value of the 5.07 education quality level as many as 57.12% of junior high schools and the rest above the value of the 5.07 education quality level of 42.88% of junior high schools. Further development of the model needs to be further developed to the level of sub-indicators so that school quality can be more specifically measured, and the data used as analysis material is expanded and enriched by other educational data from various sectors so that the model developed can be more comprehensive in measuring the achievement of education quality.