METODE QUEST DAN CHAID PADA KLASIFIKASI KARAKTERISTIK NASABAH KREDIT

Abstract

This aim of this research is to find out the classification results and to compare the magnitude of misclassification of QUEST and CHAID methods on the classification of customer of Adira Kredit Elektronik branch Denpasar. QUEST (Quick, Unbiased, Efficient Statistical Trees) and CHAID (Chi-squared Automatic Interaction Detection) are nonparametric methods that produce tree diagram which is easy to interpret. The QUEST and CHAID classification methods conclude that: 1) QUEST method produces three groups which predict customers into the current category, whereas CHAID method produces four groups which also  predict customer into the current category; 2) both methods generate the biggest classification accuracy for customers that current category which share similar characteristics; 3) both methods also have the same degree of accuracy in classifying customer data Adira Kredit Elektronik branch Denpasar.