The Use of Classification Algorithm for Forecasting the Academic Performance of Students of Biological Sciences, University of Africa, Toru-Orua
In recent years, the application of Data Mining has grown exponentially, spurred by its ability to allows us discover new, interesting and useful knowledge about data in almost every facet of discipline. Its application in education is also gaining a lot of attention across the globe. In this research, a data mining technique known as classification algorithm (Decision Tree) was used to forecast students’ academic performance. The methodology adopted in this work is the CrossIndustry Standard Process for Data Mining (CRISP-DM) which is a cyclic approach that includes six principal phases.