Classification of Gen-Z Fashion Trends Based on Tiktok Social Media Activities Using the K-Means Clustering Method - Isma Muthahharah; Hardianti Hafid (Program Studi Matematika Universitas Sulawesi Barat, 2026)
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.