Friatna, Ari (2024) Analisis Clustering Untuk Segmentasi Pelanggan Menggunakan Algoritma K-means Studi Kasus Warkop Rakyat. Other thesis, Universitas Islam Riau.
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Abstract
A deep understanding of customers is crucial for business, especially in the era of globalization. The coffee shop (warkop) industry in Indonesia not only serves as a place to enjoy coffee but also as a social space. Customer segmentation is important for warkop owners to improve service and marketing strategies. This research uses the K-Means Clustering Algorithm to analyze customer purchasing patterns at Warkop Rakyat, with the aims of analyzing purchasing patterns, identifying customer segment characteristics, and assessing the potential use of analysis results in marketing strategies and customer management. The research method used is clustering with the K-Means Algorithm. The developed system can provide cluster calculation results consistent with manual calculations without iteration limits, using randomly initialized centroids. Manual calculations show that the process requires 4 iterations, resulting in 4 data points in cluster-1, 25 data points in cluster-2, and 24 data points in cluster-3. The system's calculation results are consistent with manual calculations, proving that this system successfully aids in customer segmentation at Warkop Rakyat using the K-Means method.
| Item Type: | Thesis (Other) |
|---|---|
| Contributors: | Contribution Contributors NIDN/NIDK Sponsor Labellapansa, Ause 1018088102 |
| Uncontrolled Keywords: | Clustering, K-Means Algorithm, Customer Segmentation, Warkop Raky |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | > Teknik Informatika |
| Depositing User: | Yolla Afrina Afrina |
| Date Deposited: | 25 Sep 2025 01:25 |
| Last Modified: | 25 Sep 2025 01:25 |
| URI: | https://repository.uir.ac.id/id/eprint/30165 |
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