Multivariate Random Forest to Identify the Importance Variable of 8 National Education Standards toward National Examination of Student High School in Indonesia
Keywords:
multivariate random forest, national education standards, national examAbstract
Quality of human resources is one of the important aspect in terms of national development. One way that can be used to improve the quality of human resources in Indonesia is by improving the quality of the education. Therefore, the quality of education in Indonesia needs to be considered. The quality of education is the level of conformity between education implementers with the National Education Standards (SNP) in schools. One of the factors that is used to measure the level of success of SNP can be evaluated from National Examination (UN). Therefore it is necessary to do an analysis to find out the important factors of 8 SNP indicators which have a high influence on the UN results. The response variable is the average of national exam scores of the three main subjects tested. The response variables are numerical and multivariate and also have a high correlation between the scores of the three subjects. Based on these considerations, the Multivariate Random Forest (MRF) analysis method was applied. The results of the analysis that can be taken in this study are that the MRF method is able to identify the model stable even though it only uses training data with a cut off of 5%. The results of the analysis of importance variable from 8 variables of the national education standard toward variables of national examination scores, obtained 3 standards with the highest level of importance that are the competency standard of graduates (SKL), content standards (SI) and management standards (SPL).
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