CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS
Journal Title: Problems of Education in the 21st Century - Year 2019, Vol 77, Issue 3
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.
Authors and Affiliations
Citra Kurniawan, Punaji Setyosari, Waras Kamdi, Saida Ulfa
Keywords
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- EP ID EP590726
- DOI 10.33225/pec/19.77.349
- Views 106
- Downloads 0
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