Abstract—The purpose of this research is to recommend
appropriate courses for students which use multiple-classifier
data mining techniques to assist in the work. The process of
creating a predictive model use Weka as a tool to build a model.
Data classification techniques for finding answers and include
results from the prediction of an individual's classifier
techniques have majority votes. By segmenting the data used in
the research into three groups based on the amount of data. The
research found that recommended course, using
multiple-classifier data mining techniques has worked with
more accurate than using single data mining techniques. We
have shown that the most accurate of 72%. In addition, also
found the accuracy of the recommend is increased when the
amount of data that is used to increase.
Index Terms—Data mining, classification, multiple classifier, education.
Teerasak Sungsri is with Business Computer Program, Faculty of Management Science, Nakhon Ratchasima Rajabhat University, Thailand (e-mail: firstname.lastname@example.org).
Cite: Teerasak Sungsri, "The Use of Multiple-Classifier Data Mining Technique for Study Guideline," International Journal of Information and Education Technology vol. 8, no. 1, pp. 22-25, 2018.