Clustering Data Produk Sportswear E-Commerce Menggunakan Algoritma K-Means

Mustofa, Achmad and , Azizah Fatmawati, S.T., M.Cs. (2026) Clustering Data Produk Sportswear E-Commerce Menggunakan Algoritma K-Means. Skripsi thesis, Universitas Muhammadiyah Surakarta.

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Abstract

The rapid growth of transaction data in the sportswear category on e-commerce platforms has not been optimally utilized to support market segmentation strategies. This condition makes it difficult for business actors to identify product positioning and consumer behavior patterns amid increasingly competitive digital market conditions. Without structured data analysis, strategic decision-making related to marketing and inventory management becomes less accurate. Therefore, this study aims to conduct an in-depth analysis of sportswear product data on e-commerce platforms by applying data mining techniques through the K-Means Clustering algorithm. The data used in this study include product price, units sold, and customer rating as the main parameters. The research methodology follows the stages of the Knowledge Discovery in Databases (KDD) process, consisting of Data Selection, Preprocessing, Transformation, Data Mining, and Evaluation. To ensure the validity and quality of the clustering results, this study employed the Elbow Method and Silhouette Coefficient as the primary evaluation metrics. The results revealed three clusters: C0, characterized by low sales volume and moderate customer ratings; C1, characterized by high sales volume but low customer ratings; and C2, characterized by high sales volume and high customer ratings. Furthermore, the findings indicate that product price was not a significant distinguishing factor among clusters, whereas sales volume and customer ratings were the primary variables influencing cluster formation. These results can provide valuable insights for e-commerce businesses in developing more effective product segmentation and marketing strategies.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	E-commerce, Sportswear, Data Mining, K-Means Clustering, Product Segmentation
Subjects:	T Technology > Information Technology > Software. Aplication > Data Manajemen T Technology > Information Technology > Software. Aplication > E-Commerce
Divisions:	Fakultas Komunikasi dan Informatika > S1 Teknik Informatika
Depositing User:	ACHMAD MUSTOFA
Date Deposited:	19 Aug 2026 02:55
Last Modified:	19 Aug 2026 02:55
URI:	http://eprints.ums.ac.id/id/eprint/148430

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