Improved Chi Square Automatic Interaction Detection on Students Discontinuation to Secondary School

Abstract

Improved Chi Square Automatic Interaction Detection (CHAID) with bias correction is the developmentof the CHAID method by relying on Tschuprow’s T test calculations with bias correction in the processof forming a classification tree. This study aims to obtain a classification of factors which influencestudents for not continuing their education from junior high school or equivalent to high school orequivalent. The results obtained in the classification tree produce nine classifications. Based on theresults of the classification tree, the classification of students who do not continue their education tohigh school or equivalent is: students with disabilities who do not have access to Information andCommunication Technology (ICTs) (0.89); students who work without disability but do not have accessto ICTs (0.73); and students who do not work without disability but do not have access to in ICTs(0.60). Based on the classification obtained the factors which influence students for not continuingtheir education to high school or equivalent are access to ICTs, employment status, and persons withdisabilities. The classification accuracy of the results uses the Improved-CHAID method with biascorrection with a proportion of 80% training data and 20% testing data, namely 72.3033% on trainingdata and an increase of 73.3300% on testing data.