Home > Archive > 2018 > Volume 8 Number 1 (Jan. 2018) >
IJIET 2018 Vol.8(1): 22-25 ISSN: 2010-3689
doi: 10.18178/ijiet.2018.8.1.1006

The Use of Multiple-Classifier Data Mining Technique for Study Guideline

Teerasak Sungsri

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: mrajaab@gmail.com).


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.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net


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