Restructuring iCheating Model with Cluster Analysis on Affecting Factors of Academic Cheating Behavior

The rapid ICT advancement entails significant impacts to human life specifically in education. One of susceptible drawback of ICT is any attempt to cheat dropping the academic integrity. One of the most commonly frauds found is deceiving by using iPhone exploitable as a media to cheat in exams called as iCheating. iCheating is a form of academic cheating using iPhone. In order to properly cope with the iCheating, the education institutions need to identify factors affecting the iCheating behavior among students to anticipate earlier and to maintain the academic integrity. The objective of this research was to grant recommendations to the education institutions to minimize iCheating. The research was based on iCheating Model developed by Elodie Gentina. Data collected was to 170 students using iPhone based on three main factors observed: emotional intelligence, nomophobia and academic iCheating. Having obtained the data calculation, model restructuring was performed on clustering method using DBSCAN and K-Means algorithm to reveal broaden observations what real characteristics represent the students commit iCheating.