Implementasi Algoritma K-Means Dengan Optimasi Elbow Untuk Pengelompokkan Kepuasan Konsumen Gen Z Dalam Berbelanja Online
DOI:
https://doi.org/10.29408/jprinter.v3i2.33217Keywords:
Consumer Satisfaction, Elbow, Gen Z, K-Means, TikTok ShopAbstract
The development of digital technology has driven the increasing trend of online shopping, especially among Gen Z who actively use social media such as TikTok Shop. Therefore, it is important for business actors to understand the consumer satisfaction window to improve marketing strategies and maintain consumer loyalty. This study aims to analyze the grouping of Gen Z consumer satisfaction in East Lombok in online shopping at TikTok Shop using the K-Means algorithm and with Elbow optimization to determine the optimal number of clusters. The data used in this study were obtained by distributing questionnaires to 507 Gen Z respondents in East Lombok in 2025, with six main variables: product quality, product price, delivery, ease of application, influencer influence, and overall satisfaction. The results of the analysis using Google Colab showed the formation of three main clusters: Cluster 1 with a high level of satisfaction of 169 respondents, Cluster 2 with a moderate level of satisfaction of 255 respondents, and Cluster 3 with a low level of satisfaction of 83 respondents. Each cluster has different characteristics in assessing satisfaction variables. This information can be used as a reference for business actors on TikTok Shop in developing more effective marketing strategies
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