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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Feby Ria Syahpitri Br Ginting
STMIK KAPUTAMA
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Application of the Apriori Algorithm to Determine the Correlation of Tiktok Social Media use with the Learning Concentration of Senior High School Students Feby Ria Syahpitri Br Ginting; Marto Sihombing; Tioria Pasaribu
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 6 No. 1 (2026): October 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v6i1.2621

Abstract

Learning concentration is a crucial factor that supports the effectiveness of the learning process. Yet, the intensive use of short-video social media such as TikTok among students potentially disrupts their focus. At SMA/SMK Bina Bersaudara, students exhibit a high intensity of TikTok use, while the available student data has never been analyzed to reveal its relationship with learning concentration. This study aims to apply the Apriori algorithm, an association rule mining method in data mining, to identify patterns of relationship among student data, TikTok usage indicators, and learning concentration. The data were collected through questionnaires distributed to thirty students, transformed into binary form, and tested using RapidMiner with a minimum support of 20% and a minimum confidence of 80%. The analysis produced one valid association rule: students who open TikTok one to three times a day, most often at midday, and usually study for less than one hour per session tend to concentrate well, with a confidence level of 88.9%. The results indicate that the Apriori algorithm is able to reveal consistent relationship patterns between TikTok usage habits and learning concentration, which can serve as a data-based reference for schools, teachers, and parents in supervising social media use.
Co-Authors Marto Sihombing Pasaribu, Tioria