Improved Chi Square Automatic Interaction Detection on Student’s Discontinuation to Secondary School
Abstract
Improved Chi Square Automatic Interaction Detection (CHAID) with bias correction
is the development of the CHAID method by relying on Tschuprow's T test
calculations with bias correction in the process of forming a classification tree. This
study aims to obtain a classification of factors which influence students for not
continuing their education from junior high school or equivalent to high school or
equivalent. The results obtained in the classification tree produce nine classifications.
Based on the results of the classification tree, the classification of students who do not
continue their education to high school or equivalent is: students with disabilities
who do not have access to ICTs (0.89); students who work without disability but do
not have access to 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 continuing their education to high school or
equivalent are access to ICTs, employment status, and persons with disabilities. The
classification accuracy of the results uses the Improved-CHAID method with bias
correction with a proportion of 80% training data and 20% testing data, namely
72.3033% on training data and an increase of 73.3300% on testing data.
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