Hybrid Model Of Structural Equation Modeling Pls And Rfm (Recency, Frequency And Monetary) Model To Improve Bank Average Balance

Authors

  • Jerry Heikal Bakrie University
  • Vitto Rialialie Bakrie University
  • Deva Rivelino Raharja of University
  • Ign Agus Supriyono Raharja of University

DOI:

https://doi.org/10.34306/att.v4i1.221

Keywords:

Bank, Structural Equation Modeling, Recency, Frequency, Monetary, Business Saving Product

Abstract

As a business players, entrepreneurs certainly need bank products and supports that provide fast and easy services with wide-spread network in Indonesia. In this study, Structural Equation Model (SEM) identify the transaction that influence the average balance. The objects of the RFM segmentation on the selected transaction is to understand customer segment score and build a marketing strategy for each segment with different levels of loyalty for the Financial result of higher Average Balance. 

The segmentation results found three driver categories, High Recency, Mid Recency and Low Recency category. High Recency is considered Active customer where campaign category can be cross/up-selling and promotional accordingly with their Frequency and Monetary category. Mid Recency category is considered Risky customer where campaign category can be retention program accordingly with their Frequency and Monetary. Last, Low Recency is considered already Churn customer where campaign category is to conduct reactivation.

References

F. S. Lubis, A. P. Rahima, M. I. H. Umam, and M. Rizki, “Analisis Kepuasan Pelanggan dengan Metode Servqual dan Pendekatan Structural Equation Modelling (SEM) pada Perusahaan Jasa Pengiriman Barang di Wilayah Kota Pekanbaru,” J. Sains, Teknol. dan Ind., vol. 17, no. 1, pp. 25–31, 2020.

A. Wibowo and A. R. Handoko, “Segmentasi Pelanggan Ritel Produk Farmasi Obat Menggunakan Metode Data Mining Klasterisasi Dengan Analisis Recency Frequency Monetary (RFM) Termodifikasi,” J. Teknol. Inf. dan Ilmu Komput, 2020.

H. Rohaeni and N. Marwa, “Kualitas Pelayanan Terhadap Kepuasan Pelanggan,” J. Ecodemica, vol. 2, no. 2, 2018.

R. Oktarini, “Pengaruh Kualitas Pelayanan Dan Harga Terhadap Kepuasan Pelanggan Pengguna Jasa Aplikasi Gojek Di Kota Tangerang,” J. Sekr. Univ. Pamulang, vol. 6, no. 2, pp. 248–257, 2020.

A. Gofur, “Pengaruh kualitas pelayanan dan harga terhadap kepuasan pelanggan,” J. Ris. Manaj. Dan Bisnis Fak. Ekon. UNIAT, vol. 4, no. 1, pp. 37–44, 2019.

E. D. Supandi, “Pengaruh Remunerasi dan Motivasi Terhadap Kinerja Pegawai UIN Sunan Kalijaga Yogyakarta dengan Menggunakan Structural Equation Modelling,” in PRISMA, Prosiding Seminar Nasional Matematika, 2020, vol. 3, pp. 84–94.

I. Ilamsyah, R. Wulandari, and R. R. Fahreza, “Web Design Visual Comic Communication As A Visual Based Learning Media,” IAIC Trans. Sustain. Digit. Innov., vol. 2, no. 1, pp. 1–10, 2020.

N. Hermansyah, “Model Pengukuran Kualitas Layanan Nasabah Mesin Hybrid Bank BRI Dengan Metode Structural Equation Model (SEM),” J. Ilm. Humanika, vol. 3, no. 3, pp. 53–58, 2020.

Y. H. Chrisnanto and A. Kanianingsih, “Pengelompokan Ekuitas Pelanggan Berbasis Recency Frequency Monetary (RFM) Menggunakan K-Means Clustering.” vol, 2019.

N. R. Syarif and W. Windarto, “Implementasi Algoritma Fuzzy C-means Dan Metode Recency Frequency Monetary (Rfm) Pada Aplikasi Data Mining Untuk Pengelompokan Pelanggan,” Sebatik, vol. 22, no. 2, pp. 88–94, 2018.

A. Suryadi, P. T. Asmoro, and A. Solihin, “Hybrid Electric Power Plant Using Wind Turbine Savonius Helix and Solar Cell as an Alternative Power Source in the Lightning Tower at Flashing Lights,” ADI J. Recent Innov., vol. 1, no. 1, pp. 1–6, 2019.

N. Lutfiani, U. Rahardja, and I. S. P. Manik, “Peran Inkubator Bisnis dalam Membangun Startup pada Perguruan Tinggi,” J. Penelitan Ekon. dan Bisnis, vol. 5, no. 1, pp. 77–89, 2020.

M. Darwin and K. Umam, “Indirect Effect Analysis on Structural Equation Modeling (Comparative Study of Using Amos and SmartPLS Software),” Nucleus, vol. 1, no. 02, pp. 50–57, 2020.

A. U. Zaelani, T. Husain, and A. Budiyantara, “Analisis Simulasi Sistem Penunjang Keputusan: Model Matematis Dengan Pendekatan Goodness-of Fit Berbasis Structural Equation Model,” SMARTICS J., vol. 6, no. 1, pp. 10–16, 2020.

R. Latumeten, Y. A. Lesnussa, and F. Y. Rumlawang, “Penggunaan Structural Equation Modeling (Sem) untuk Menganalisis Faktor yang Mempengaruhi Loyalitas Nasabah (Studi Kasus: PT Bank Negara Indonesia (BNI) KCU Ambon),” Sainmatika J. Ilm. Mat. dan Ilmu Pengetah. Alam, vol. 15, no. 2, pp. 76–83, 2018.

M. T. Daulay and A. Sanny, “Analysis of Structural Equation Modeling Towards Productivity and Welfare of Farmer’s Household in Sub-District Selesai of Langkat Regency,” Int. J. Res. Rev., pp. 117–123, 2019.

C. Andreas, S. Priandi, A. N. M. B. Simamora, and M. F. F. Mardianto, “Analisis Hubungan Media Sosial dan Media Massa dalam Penyebaran Berita Hoaks berdasarkan Structural Equation Modeling-Partial Least Square,” MUST J. Math. Educ. Sci. Technol., vol. 6, no. 1, pp. 81–96, 2021.

S. K. Mariniharsi, T. Hidayati, and I. Tricahyadinata, “Pengaruh karakteristik individu dan karakteristik pekerjaan terhadap kepuasan kerja serta kinerja pegawai negeri sipil,” J. Ilmu Manaj. Mulawarman, vol. 4, no. 1, 2020.

E. Erfiansyah and R. Rustandi, “ANALISIS MANFAAT AUDIT DITINJAU DARI PERSPEKTIF KLIEN AUDIT,” J. Ilm. MEA (Manajemen, Ekon. Akuntansi), vol. 2, no. 3, pp. 68–83, 2018.

M. I. Sanni and D. Apriliasari, “Blockchain Technology Application: Authentication System in Digital Education,” Aptisi Trans. Technopreneursh., vol. 3, no. 2, pp. 37–48, 2021.

D. Himawati, “Pengaruh Word of Mouth dan Manfaat Terhadap Keputusan Menggunakan E-Wallet Dana Melalui Kepercayaan Pelanggan di Jabodetabek,” INOBIS J. Inov. Bisnis dan Manaj. Indones., vol. 4, no. 3, pp. 424–436, 2021.

K. Arora and A. S. Bist, “Artificial intelligence based drug discovery techniques for covid-19 detection,” Aptisi Trans. Technopreneursh., vol. 2, no. 2, pp. 120–126, 2020.

A. Febriani and S. A. Putri, “Segmentasi Konsumen Berdasarkan Model Recency, Frequency, Monetary dengan Metode K-Means,” J. Ind. Eng. Manag. Syst., vol. 13, no. 2, 2020.

Y. O. Pailan, Y. H. Chrisnanto, and A. I. Hadianna, “Segmentasi Loyalitas Pelanggan Berbasis RFM (Recency, Frequency, Monetary) Menggunakan K-Means pada PD. Persada Ikan,” Pros. SISFOTEK, vol. 4, no. 1, pp. 167–171, 2020.

S. Bin Kamarudin and M. S. Taat, “Pengaruh Faktor-faktor Tekanan Kerja dalam kalangan Guru di Sekolah Menengah: Satu Analisis Persamaan Struktur (SEM-PLS),” Malaysian J. Soc. Sci. Humanit., vol. 5, no. 11, pp. 104–115, 2020.

S. I. Murpratiwi, I. G. A. Indrawan, and A. Aranta, “ANALISIS PEMILIHAN CLUSTER OPTIMAL DALAM SEGMENTASI PELANGGAN TOKO RETAIL,” J. Pendidik. Teknol. dan Kejuru., vol. 18, no. 2, pp. 152–163, 2021.

M. Khatami, A. Alexander, and R. B. Alfarizky, “PAK BEN: INOVASI APLIKASI E-COMMERCE BAGI UMKM BENGKEL DAN BENSIN ECERAN DALAM MENCAPAI SUSTAINABLE DEVELOPMENT GOALS 2030,” J. Ilm. Penal. dan Penelit. Mhs., vol. 5, no. 2, pp. 158–178, 2021.

A. Khatoon, “A blockchain-based smart contract system for healthcare management,” Electron., vol. 9, no. 1, 2020, doi: 10.3390/electronics9010094.

F. Agustin, Q. Aini, A. Khoirunisa, and E. A. Nabila, “Utilization of Blockchain Technology for Management E-Certificate Open Journal System,” Aptisi Trans. Manag., vol. 4, no. 2, pp. 133–138, 2020.

Downloads

Published

2021-12-14

How to Cite

Jerry Heikal, Vitto Rialialie, Rivelino, D., & Ign Agus Supriyono. (2021). Hybrid Model Of Structural Equation Modeling Pls And Rfm (Recency, Frequency And Monetary) Model To Improve Bank Average Balance . Aptisi Transactions on Technopreneurship (ATT), 4(1), 1–8. https://doi.org/10.34306/att.v4i1.221

Issue

Section

Articles