Journal of System and Computer Engineering
Vol 6 No 1 (2025): JSCE: January 2025

Evaluating the Effectiveness of Online Learning Methods with a Probabilistic Naive Bayes Approach

Butsiarah, Butsiarah (Unknown)
Rijal, Muhammad (Unknown)



Article Info

Publish Date
24 Jan 2025

Abstract

Online learning methods become an important element in supporting the flexibility and effectiveness of teaching and learning process, especially through approaches such as Video Tutorial, Virtual Discussion, and Self-paced Reading. This research aims to evaluate the effectiveness of the three methods in improving students' engagement, comprehension, and learning motivation by utilizing Naive Bayes algorithm. The dataset used includes student data taken through questionnaires and teacher evaluation results, with variables such as material suitability, engagement, ease of access, and student exam results. Through this approach, the research is able to predict the learning method that best suits students' needs based on the analyzed variables. The results show that Video Tutorial is the most effective method in supporting students' understanding and motivation. The implementation of this research is expected to help the development of a better online learning system in improving students' learning experience, and provide practical recommendations for educators in choosing the right learning method.

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Journal Info

Abbrev

JSCE

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Programming Languages Algorithms and Theory Computer Architecture and Systems Artificial Intelligence Computer Vision Machine Learning Systems Analysis Data Communications Cloud Computing Object Oriented Systems Analysis and Design Computer and Network Security Data ...