Rasya Alya Trismia, . (2025) CLUSTERING LOYALITAS PELANGGAN MENGGUNAKAN ALGORITMA K-MEANS BERDASARKAN DATA TRANSAKSI PENJUALAN PT SINAR EKA SELARAS TBK. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
The increasing use of electronic devices and their accessories has intensified competition in the retail industry, including for PT Sinar Eka Selaras. To retain customers and enhance loyalty, companies need a data-driven approach to understand customer transaction patterns. This study aims to cluster customer loyalty based on sales transaction data from January to July 2024 using the K-Means algorithm. The dataset consists of 125.274 rows that underwent data selection, data preprocessing, and data transformation. Three main variables were analyzed: ‘Quantity’, ‘Total Nett Amount with Tax’, and ‘Transaction Frequency’. The Elbow method was used to determine the optimal number of clusters, which was found to be three. The clustering result was evaluated using the Davies-Bouldin Index (DBI), which produced a score of 0.3867, indicating a reasonably good clustering quality. The clustering results categorized customers into three groups: non-loyal customers (Cluster 0), potential customers (Cluster 1), and loyal customers (Cluster 2). Visualization techniques such as pie charts, bar charts, line charts, and heatmaps were used to illustrate each cluster's characteristics based on purchase trends, brand and category preferences, payment methods, and customer locations. This study is expected to provide an overview of customer loyalty levels and serve as a foundation for developing follow-up marketing strategies to retain existing customers and drive future sales growth.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2110512146] [Pembimbing 1: Ruth Mariana Bunga Wadu] [Pembimbing 2: M. Octaviano] [Penguji 1: Ika Nurlaili Isnainiyah] [Penguji 2: Mohamad Bayu Wibisono] |
| Uncontrolled Keywords: | customer loyalty, K-Means clustering, Elbow method, Davies-Bouldin Index, transaction data |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1) |
| Depositing User: | RASYA ALYA TRISMIA |
| Date Deposited: | 07 Aug 2025 01:19 |
| Last Modified: | 07 Aug 2025 01:19 |
| URI: | http://repository.upnvj.ac.id/id/eprint/37358 |
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