Analysis of Multivariate Adaptive Regression Spline (MARS) Model in Classifying factors affecting on Student the Study Period at FKIP Darussalam University of Ambon

Abstract

This study aims to determine the applicative model that can be revealed through the Multivariate Adaptive Regression Spline (MARS) classification Model for the problems alumni study period of the FKIP Darussalam University of Ambon. To find out the applicative model that can be revealed through the MARS classification model, parameter estimation is first performed to find the best MARS model. The best MARS model is chosen based on the minimum generalized cross validation (GCV) value.The research result indicates that the parameter estimation of MARS model using Ordinary Least Square (OLS) method obtained were convergent. This is indicated by the smallest of value Mean Square Error (MSE). In addition, the application of the MARS model using the OLS method on data alumni study period of the FKIP Darussalam University of Ambon, result indicates that there is an influential base function, BF3 which contains two predictor variable, that is first semester achievement index and family economics conditions. This is caused by BF3 has a significance value tcount > ttable so the decision taken is to reject H0 which means that the BF3 basis function parameter has a significant effect on the model.