Issue |
E3S Web Conf.
Volume 317, 2021
The 6th International Conference on Energy, Environment, Epidemiology, and Information System (ICENIS 2021)
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Article Number | 05027 | |
Number of page(s) | 10 | |
Section | Information System Management and Environment | |
DOI | https://doi.org/10.1051/e3sconf/202131705027 | |
Published online | 05 November 2021 |
Intelligent Tutoring System Using Bayesian Network for Vocational High Schools in Indonesia
1 Magister Program of Information System, Postgraduate School, Diponegoro University, Semarang, Indonesia
2 Faculty of Information Technology, Satya Wacana Christian University, Salatiga, Indonesia
3 Department of Physics, Faculty of Science and Mathematics, Diponegoro University, Semarang, Indonesia
* Corresponding author: ikhewan29@students.undip.ac.id
The lack of personal tutorials during school hours caused the learning approach at Vocational High Schools to be less optimal, and the student's competence is not achieved maximumly. Some computer-based self-learning systems have been developed as solutions to these problems. Unfortunately, the system's weakness is that learning does not pay attention to the diversity of students' abilities. Based on those, this research proposes an Intelligent Tutoring System (ITS) model using Bayesian Network at Vocational High Schools (SMK) to determine the level of students' abilities and teach skills competency materials based on each student's ability level. This is quantitative research with quasi-experimental using one group pretest-posttest design. The research participants were 69 students of the Computer and Network Engineering expertise program at SMK Negeri 4 Gowa and SMK Negeri 1 Gowa, South Sulawesi Province, Indonesia. The results showed significant differences in students' learning outcomes after the use of the proposed ITS; in other words, the proposed ITS was effective in increasing the skill competency of Vocational High School Students. The evaluation results showed that the created Bayesian Network model had a high level of accuracy, reaching 84%.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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