CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS

TitleCLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS
Publication TypeJournal Article
Year of Publication2019
AuthorsKurniawan, C, Setyosari, P, Kamdi, W, Ulfa, S
JournalProblems of Education in the 21st Century
Volume77
Issue3
Start Page349-363
PaginationContinuous
Date PublishedJune/2019
Type of ArticleOriginal article
ISSN1822-7864
Other NumbersE-ISSN 2538-7111
Keywordsdata mining, self-efficacy, visual-verbal preferences
Abstract

The purpose of this research was to build a classification model and to measure the correlation of self-efficacy with visual-verbal preferences using data mining methods. This research used the J48 classifier and linear projection method as an approach to see patterns of data distribution between self-efficacy and visual-verbal preferences. The measurement of the correlation of engineering students' self-efficacy with visual-verbal preferences using the data mining method approach gets the result that self-efficacy does not correlate with visual-verbal preferences. However, engineering students' self-efficacy influences the achievement of initial learning outcomes. Visual-verbal preference is more influenced by students' interest in images so it can be concluded that self-efficacy affects the initial results of learning but does not have a correlation with visual-verbal preferences. The results of the decision tree provide the results that are easily understood and present a correlation between self-efficacy and visual-verbal preferences in a visual form.

URLhttp://oaji.net/articles/2019/457-1561381997.pdf
DOI10.33225/pec/19.77.349
Refereed DesignationRefereed
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