Pemodelan Terhadap Kelulusan Siswa Masuk Kelas Akselerasi Menggunakan Analisis Regresi Logistik Dan Multivariate Adaptive Regression Spline (MARS)
Abstract
Regression Analysis is a statistical methodology that usually used for analyzing the relationship between a response and one or more predictor. When the response is categorical variable, then the regression methods that could be used are Logistic Regression and Multivariate Adaptive Regression Spline (MARS). The result of both modeling can be used to classify the objects. The aim of this research is to find a quantitative model for explaining factors that influenced the success of students in joining the acceleration class. Evaluation the accuracy of classification rate is done by implementing Press Q statistic test. The result of Logistic Regression shows that the classification accuracy is 74,8 where as MARS yields 77,7. Hence, MARS model is the best model for evaluating the success factor of student in joining the acceleration class.
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