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 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 Information and
Communication Technology (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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