Data mining in the education sector is predominantly used to predict, group, model, and monitor 
various learning activities using techniques such as classification, clustering, association rules, 
statistics, and visualization (Aldowah, Al-Samarraie, & Fauzy, 2019). EDM is a process for 
addressing important educational questions using DM techniques applied to specific datasets 
originating from educational environments (Romero & Ventura, 2013). In Romero and 
Ventura’s review (2013) on EDM, they figured out a cycle (Figure 1) about how DM in 
educational environments is applied. The items in EDM lifecycle have educational systems as 
source of data; ie traditional classrooms, e-Learning environments, data mining tools and 
methods; ie Python, Weka, RapidMiner, etc. and classification, clustering and directions of 
meaningful information gained are students, educators and responsible administrators.