Customer Loyalty Analysis Using Recency,Frequency, Monetary (RFM) and K-means Cluster for Labuan Bajo Souvenirs in Online Store

  • Supangat Supangat Universitas 17 Agustus 1945, Indonesia
  • Yosevina Mulyani Universitas 17 Agustus 1945, Indonesia
DOI: 10.51519/journalisi.v5i1.421
Keywords: Online Shop, RFM, K-means, Coustomer Segmentation

Abstract

An average Labuan Bajo souvenir shop sells a variety of souvenirs specific to Labuan Bajo. However, the sales process is still manual, with the shop resorting to telephone or WhatsApp communication to connect with customers for placing orders. To increase sales, typical souvenir shops in Labuan Bajo are interested in adopting effective marketing strategies. Consequently, an automated system is necessary to manage customers. The Recency, Frequency, and Monetary Analysis methods are commonly used for assigning values or weights to customers during transactions. These weights are then analyzed and grouped using k-means. Recent data analysis over the last three months reveals that the typical Labuan Bajo souvenir shop has one regular customer, three potential customers, and six regular customers. Testing the system's features showed that it was functioning correctly, and therefore, it can assist the typical Labuan Bajo souvenir shop in streamlining the sales process.

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References

S. S. Prasetyo, M. Mustafid, and A. R. Hakim, “Penerapan Fuzzy C-Means Kluster Untuk Segmentasi Pelanggan E-Commerce Dengan Metode Recency Frequency Monetary (RFM),” Jurnal Gaussian, vol. 9, no. 4, pp. 421–433, Dec. 2020, doi: 10.14710/j.gauss.v9i4.29445.

J. Jamal and D. Yanto, “Analisis RFM dan Algoritma K-Means untuk Clustering Loyalitas Customer,” Jurnal Energy, vol. 9, no. 1, pp. 1–8, May 2019.

W. A. Taqwin, N. Y. Setiawan, and F. A. Bachtiar, “Analisis Segmentasi Pelanggan dengan RFM Model pada PT. Arthamas Citra Mandiri Menggunakan Metode Fuzzy C-Means Clustering,” Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 3, no. 2, pp. 1986–1993, Feb. 2019.

Sudriyanto, “Clustering Loyalitas Pelanggan dengan Metode RFM (Recency, Frequency, Monetary) dan Fuzzy C-Means,” in SNATIF, 2017, pp. 815–822.

Sandi, T. A. Armawan, M. Raharjo, J. L. Putra, and R. Ridwan, “Clustering Kesetian Pelanggan denan Model RFM (Recency, Frequency, Monetary) dan K-Means,” Jurnal Pilar Nusa Mandiri, vol. 14, no. 2, 2018.

Waroka, Lia, S. Monalisa, D. Anjainah, and N. Arifin, “Implementasi Algoritma Fuzzy C-Means (FCM) dalam Pengklasterisasian Nilai Hidup Pelanggan Dengan Model LRFM,” Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi, vol. 6, no. 1, 2020.

A. T. Widiyanto and A. Witanti, “Segmentasi Pelanggan Berdasarkan Analisis RFM Menggunakan Algoritma K-Means Sebagai Dasar Strategi Pemasaran (Studi Kasus PT Coversuper Indonesia Global),” Konstelasi: Konvergensi Teknologi dan Sistem Informasi, vol. 1, no. 1, pp. 204–215, Apr. 2021, doi: 10.24002/konstelasi.v1i1.4293.

R. Y. Firmansah, J. Dedy Irawan, and N. Vendyansyah, “Analisis Rfm (Recency, Frequency And Monetary) Produk Menggunakan Metode K-Means,” JATI (Jurnal Mahasiswa Teknik Informatika), vol. 5, no. 1, pp. 334–341, Feb. 2021, doi: 10.36040/jati.v5i1.3282.

Novendri, “Pengertian Web,” Lentera Dumai, vol. 10, no. 2, pp. 46–57, 2019.

Supriyono, “Software Testing with the Approaach of Blackbox Testing on the Academic Information System,” International Journal of Information System & Technology, vol. 3, no. 2, pp. 227–233, 2020.

N. N. N. Nurliza, “Penerapan Euclidean Distance pada Pengenalan Pola Citra Sidik Jari,” Universitas Islam Indonesia, Yogyakarta, 2018.

S. Ahmad, and I. Effendy. "Implementasi Model View Controller (Mvc) Pada Pengembangan Sistem Informasi Pengaduan Masyarakat Pada Polres Pagaralam." Jurnal Informatika 20, no. 2 (2020): 199-208. doi: 10.30873/ji.v20i2.2393

Published
2023-03-07
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How to Cite
Supangat, S., & Mulyani, Y. (2023). Customer Loyalty Analysis Using Recency,Frequency, Monetary (RFM) and K-means Cluster for Labuan Bajo Souvenirs in Online Store. Journal of Information Systems and Informatics, 5(1), 285-299. https://doi.org/10.51519/journalisi.v5i1.421
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Vol 5 No 1 (2023): Journal of Information Systems and Informatics
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Articles

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