JAWHARAH, FAIRUZ (2025) Klasterisasi Menggunakan Algoritma K-Means dan Model Recency, Frequency, Monetary untuk Segmentasi Pelanggan (Studi Kasus: Rayu Manis). Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
Understanding customer behavior is a critical component in developing effective and sustainable marketing strategies. This study aims to segment customers of Rayu Manis, a culinary business based in Surabaya, by implementing the Recency, Frequency, Monetary (RFM) model in combination with the K-Means clustering algorithm. Transactional data collected from February 2023 to October 2024 underwent several processing stages, including data preprocessing, RFM scoring, logarithmic transformation, normalization, determination of the optimal number of clusters using the Elbow method, and evaluation using the Silhouette Score and Davies-Bouldin Index. The clustering results revealed that the Sheet Order dataset formed two clusters with a Silhouette Score of 0.51285, while the Sheet Rayu Manis dataset yielded two clusters with a Silhouette Score of 0,40095. The resulting segmentation identified groups of loyal and at-risk customers, providing a data driven foundation for targeted marketing strategies and supporting strategic decision-making within the context of small and medium-sized enterprises.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) > T58.6-58.62 Management Information Systems | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||||||
| Depositing User: | Fairuz Jawharah Jawharah | ||||||||||||
| Date Deposited: | 25 Jul 2025 02:31 | ||||||||||||
| Last Modified: | 25 Jul 2025 02:31 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/40844 |
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Klasterisasi Menggunakan Algoritma K-Means dan Model Recency, Frequency, Monetary untuk Segmentasi Pelanggan (Studi Kasus: Rayu Manis). (deposited UNSPECIFIED)
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