Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Mathematics: Theory and Applications
Isma Muthahharah
Department of Statistics, Universitas Negeri Makassar
Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Classification of Gen-Z Fashion Trends Based on Tiktok Social Media Activities Using the K-Means Clustering Method Isma Muthahharah; Hardianti Hafid
Journal of Mathematics: Theory and Applications Vol. 8 No. 1 (2026): Volume 8 Nomor 1 Tahun 2026
Publisher : Program Studi Matematika Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/jomta.v8i1.6302

Abstract

Fashion trends continue to evolve as times, culture and technology change. With social media playing a big role in its spread, especially among Generation Z (Gen-Z). This study aims to classify Gen-Z dressing trends based on their activities on TikTok using the K-Means Clustering method. Data was collected through web scraping techniques from the TikTok platform, including variables such as the number of likes, comments, shares, saves, and fashion-related hashtags. The clustering results showed three main clusters: cluster 1 consists of posts with very high engagement and viral tendencies, dominated by scene trends supported by major influencers. Cluster 2 has medium engagement with still dominant scene trends but comes from medium-sized accounts. Meanwhile, cluster 3 consists of posts with low engagement, dominated by casual styles that don't attract much attention. Overall, the results show that the success of Gen-Z dressing trends on social media is influenced by visual factors, the role of influencers, and interactive elements in the content.
Co-Authors Hardianti Hafid