@article {1215,
	title = {CLASSIFICATION OF ENGINEERING STUDENTS{\textquoteright} SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS},
	journal = {Problems of Education in the 21st Century},
	volume = {77},
	year = {2019},
	month = {June/2019},
	pages = {Continuous},
	type = {Original article},
	chapter = {349-363},
	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{\textquoteright} 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{\textquoteright} self-efficacy influences the achievement of initial learning outcomes. Visual-verbal preference is more influenced by students{\textquoteright} 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.},
	keywords = {data mining, self-efficacy, visual-verbal preferences},
	issn = {1822-7864},
	doi = {https://doi.org/10.33225/pec/19.77.349},
	url = {http://oaji.net/articles/2019/457-1561381997.pdf},
	author = {Citra Kurniawan and Punaji Setyosari and Waras Kamdi and Saida Ulfa}
}
