MACHINE LEARNING TECHNIQUE FOR ANALYZING STUDENT INTEREST IN USING TIKTOK IN THE NEW E-LEARING SYSTEM DURING THE COVID-19 PANDEMIC

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

The prolonged COVID-19 pandemic has forced the world of education to change the method of delivering material from face-to-face to online. This change has had a big impact on both students and educators, one of which is student anxiety to take part in online learning and the difficulties experienced when studying independently while online. Tiktok is a social media platform that is currently booming and loved by the younger generation, which offers live sessions and can upload short videos. The advantages of tiktok can be used as a means to mingle and motivate students to take part in online learning. Besides that, the emotions of TikTok users when they see videos on TikTok have been carried out and it is known that users of productive age are more emotional. Several previous studies have conducted an analysis of the use of Tiktok using the questionnaire method. However, the questionnaire method cannot capture information about the emotions of e-learning system users. In addition, the use of a questionnaire as a media analysis is also less effective and requires more time to carry out the calculation process. From the research results it is known that students do not like the learning method with TikTok. This is corroborated by the accuracy rate of the Naïve Bayes method which reaches 80.32%.

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Keywords

E-Learning, Tiktok, Student Opinion, Machine Learning