<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Citra Kurniawan</style></author><author><style face="normal" font="default" size="100%">Punaji Setyosari</style></author><author><style face="normal" font="default" size="100%">Waras Kamdi</style></author><author><style face="normal" font="default" size="100%">Saida Ulfa</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">CLASSIFICATION OF ENGINEERING STUDENTS' SELF-EFFICACY TOWARDS VISUAL-VERBAL PREFERENCES USING DATA MINING METHODS</style></title><secondary-title><style face="normal" font="default" size="100%">Problems of Education in the 21st Century</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data mining</style></keyword><keyword><style  face="normal" font="default" size="100%">self-efficacy</style></keyword><keyword><style  face="normal" font="default" size="100%">visual-verbal preferences</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://oaji.net/articles/2019/457-1561381997.pdf</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">77</style></volume><pages><style face="normal" font="default" size="100%">Continuous</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Original article</style></work-type><section><style face="normal" font="default" size="100%">349-363</style></section></record></records></xml>