K-Means and K-NN Methods For Determining Student Interest

Guslendra, Guslendra and Defit, Sarjon (2022) K-Means and K-NN Methods For Determining Student Interest. International Journal Of Artificial Intelegence Research, 6 (1).

Text S2-IJAIR-Juni 2022.pdf Download (687kB)

Abstract

Putra Indonesia University 'YPTK' Padang's Department of Information Systems, Faculty of Computing Science has three specializations, namely Information Technology Management, Business Information Systems and Industrial Information Systems. In the fifth semester, the acquisition of specializations takes place. In the next semester the selection of specialist programs will be determined. The option of the degree is adapted to students' needs and capacities. The acquisition of results generated in the previous semester can be seen. The objective of this survey is to provide students with suggestions for collection of degrees. The study was performed using K�Means and K-Nearest Neighbor methods in order to obtain classification of students and the correlation between recent cases and past cases. This analysis uses 13 characteristics, of which 12 are predictors and 1 is the option. The test results can be used as a way to suggest the student preferences based on preset attributes through the K-Means and K-NN methods

Actions (login required)

View Item