Analisis Regresi Logistik Multinomial Bayes untuk Pemodelan Minat Peserta Didik MAN 2 Samarinda Tahun Ajaran 2018/2019

Abstract

Currently, Senior High School and Madrasah Aliyah have implemented student specialization. The specialization includes Natural Science, Social Science and Language. There are several criteria for determining interest in Senior High School and Madrasah Aliyah which include academic scores, student interests and IQ. The multinomial logistic regression model is used to examine these factors because the dependent variable has more than 2 categories. Bayes method is used to estimate the parameters of the multinomial logistic regression. The Bayesian method is a parameter estimation technique that combines the likelihood and prior distribution function. The estimation with the Bayesian method was solved using Markov Chain Monte Carlo simulation (MCMC) with the Gibbs Sampler algorithm. The data used were new students at MAN 2 Samarinda on 2018/2019 with the results of interest namely Natural Science, Social Science and Language. Independent variables were used, namely the score of the Junior High School in subjects Natural Science, Social Science, Language and the rate of National Test. The results of modeling and analysis showed that the factors that significantly influenced were the score of the junior high school in the subject of Natural Science and the rate of National Test. The classification accuracy of the model was 63,10%.