Research Article
Design of Student Modeling System to Support Adaptive E-Learning
@INPROCEEDINGS{10.4108/eai.5-11-2022.2326520, author={Prawidya Destarianto and Khafidurrohman Agustianto and Enik Rukiati and Tanti Kustiari}, title={Design of Student Modeling System to Support Adaptive E-Learning }, proceedings={Proceedings of the 3rd International Conference on Social Science, Humanity and Public Health, ICoSHIP 2022, 05-06 November 2022, Banyuwangi, East Java, Indonesia}, publisher={EAI}, proceedings_a={ICOSHIP}, year={2023}, month={1}, keywords={student modeling k-means nbc}, doi={10.4108/eai.5-11-2022.2326520} }- Prawidya Destarianto
Khafidurrohman Agustianto
Enik Rukiati
Tanti Kustiari
Year: 2023
Design of Student Modeling System to Support Adaptive E-Learning
ICOSHIP
EAI
DOI: 10.4108/eai.5-11-2022.2326520
Abstract
Based on the results of the study, it was found that the practice of using ELearning at Politeknik Negeri Jember was only used to distribute material and collect assignments, even though there was an exam function which was widely used during the pandemic. However, the implementation of E-Learning like this is far from the learning concept being implemented by the institution, namely student-centered learning (problem and project-based learning). This study used learning motivation variables indicated by the students‘ interaction with E-Learning for clustering (K-Means) and classification (Naive Bayes). The results of the research showed that the accuracy value was 91.66%. As a result, the researchers are optimistic that the results of this study can be used to optimize the learning process at Politeknik Negeri Jember.