Abstract—The analysis of student behavior affecting the
learning results with that data mining is research. To find
behavioral factors that affects the student's academic
performance. Learn more by the research team leading the
reference information from collecting data from questionnaires
of students of the Faculty of Science. To analyze the model of
decision making to separate groups with similar behavior
together and use grouping techniques (Clustering). Making
decision to find out answers to behavioral factors that affect
learning results. In small groups based on various behavioral
factors such as Use of free time in everyday life Learning
anxiety Concentrate on learning Motivation for learning and
using K - Means Cluster and Random Tree to find a model that
has Correctly Classified Instances when tested with 380
datasets of training data, with an average of 98% which is the
average at a good level can Bring the model that has been
Continued to develop the system.
Index Terms—Study behavior, learning results, data mining techniques, k-means, random tree.
The author is with Computer Science and Information Technology Department, Faculty of Science at Sriracha, Kasetsart University Sriracha Campus Chonburi, Thailand (e-mail: firstname.lastname@example.org, email@example.com).
Cite: Supaporn Bundasak, "Student Behavior Analysis Affecting Learning Achievement of Information Technology and Computer Science Students," International Journal of Machine Learning and Computing vol. 10, no. 2, pp. 346-351, 2020.Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).