Perbandingan Hasil Klasifikasi Menggunakan Regresi logistik dan Analisis Diskriminan Kuadratik Pada Kasus Pengklasifikasian Jurusan Di SMA Negeri 8 Samarinda Tahun Ajaran 2014/2015 - Cristine Uli Artha; Yuki Novia Nasution; Ika Purnamasari (Program Studi Statistika FMIPA Universitas Mulawarman, 2016)
Logistic Regression Analysis and Discriminant Analysis represent the statistical method for the classification of a number of object. In the case of classification especially if there's only two response categories, logistic regression is used more precisely if the assumption of multivariate normality in data cannot be fullfiled. The assumption of normality multivariate distribution and equality of variance covariance matrices represent the important matter in discriminant analysis for getting of high accuracy of classification. Discriminant analysis method that is used in inequality of variance covariance matrices is called quadratic discriminant analysis. The purpose of this study was to determine the classification results by using Logistic Regression and Quadratic Discriminant Analysis and compares the classification accuracy. The data that is used in the study is the average raport of the first and second semester of the class X at SMA Negeri 8 Samarinda academic year 2014/2015. Data consists of 190 students with two independent variables and four dependent variables. Based on research results, obtained results for the value of class accuracy is Logistic Regression 83.16% and Quadratic Discriminant Analysis 84.21%.