IMPLEMENTATION OF K-MEANS ALGORITHM FOR INFORMATION TECHNOLOGY FRESHMAN CLASS DIVISION

Abstract

Almost all universities divide their IT freshman into classes randomly or based on students score, either their score during the selection test held by the university or National Examination score. Universities often find case that a class consists of all ‘smart’ students and a class consists of all ‘lazy’ students. This thesis intends to create an application to help universities divides their Information Technology freshman into classes based on freshman competency and experience about Information Technology (IT) on the senior high school. The experiment is conducted by collecting data IT students who are not in the first semester. The data consists of their experience about IT as well as other knowledge fields and their current GPA. The results of the experiment show that from 50 data samples collected, the application correctly predicts 34 students GPA range based on respondents competency with IT and other knowledge fields during their study in senior high school.