The Effect of The Number of Attributes On The Selection of Study Program Using Classification and Regression Trees Algorithms

Abstract

Proper selection of diciplines/programs of study is a vital task for student. Therefore a decission support system is highly demanded to help prospective students to decide the right choice. Considered factors in taking the programs of study selection are vary among people. Determining the best combination of atributes to achieve the best selection to support prospective students is important. We use student data and it's atributes as well as their choice as a dataset. This research implements classification algorithm and regression trees (CART). An Evaluation of CART algorithm using combination of 3,4,5 and 6 available students data atributes has been carried out. According to the experiments, 5 atributes achieve the best accuracy at 86%, while 6, 4 and 3 atributes yielded worse accuracy at 80%,70% and 56% respectively.