Selection of the Best Customer using a Combination of Rank Order Centroid and Grey Relational Analysis

Muhammad Waqas Arshad(1), Yuri Rahmanto(2), Setiawansyah Setiawansyah(3*),

(1) University of Bologna
(2) Universitas Teknokrat Indonesia, Lampung
(3) Universitas Teknokrat Indonesia, Lampung
(*) Corresponding Author

Abstract


A customer is an individual or entity that purchases goods or services from a company or organization. They play an important role in business success, as customer satisfaction and loyalty can determine a company's reputation and sustainability in the marketplace. One of the main challenges is collecting and analyzing accurate and comprehensive data regarding purchase behavior, transaction frequency. Other challenges include keeping customer data confidential and ensuring that the selection process is fair and transparent. The ROC method is used in the initial stage to determine the importance weight of each criterion based on the subjective ranking of the decision makers, which is then converted into numerical weights systematically and consistently, the GRA method is applied to calculate the relational proximity between each customer's alternative to the ideal solution based on their performance values on each criterion.The purpose of this study is to develop and implement a comprehensive framework for the selection of the best customers by combining ROC weighting and GRA methods, and provide practical recommendations for companies in managing and utilizing the best customer relationships, in order to improve customer loyalty and long-term profitability. By combining these approaches, businesses can effectively prioritize customers based on their significance and potential to build long-term relationships and maximize profitability, thus enabling more targeted marketing strategies and better resource allocation. The best customer ranking results were obtained by Customer I with a final GRG value of 0.1792 for the 1st rank, Customer D with a final GRG value of 0.1683 for the 2nd rank, and Customer K with a final GRG value of 0.1505 for the 3rd rank


Keywords


Customer Loyalty; GRA; Recommendations; ROC; Selection

Full Text:

PDF

References


S. Rahnamay Bonab, S. Jafarzadeh Ghoushchi, M. Deveci, and G. Haseli, “Logistic autonomous vehicles assessment using decision support model under spherical fuzzy set integrated Choquet Integral approach,” Expert Syst. Appl., vol. 214, p. 119205, Mar. 2023, doi: 10.1016/j.eswa.2022.119205.

A. Sani, S. Aisyah, M. Rachmawati, D. P, and N. Wiliani, “Analysis Of Decision Support Systems for Candidate Selection Scholarship Recipients Using TOPSIS Method,” in Proceedings of the 2nd International Conference on Law, Social Science, Economics, and Education, ICLSSEE 2022, 16 April 2022, Semarang, Indonesia, 2022. doi: 10.4108/eai.16-4-2022.2320136.

K. Harianto, I. Arfyanti, and A. Yusika, “Penerapan Metode MOORA pada Sistem Pendukung Keputusan Pemilihan Kepala Laboran,” Build. Informatics, Technol. Sci., vol. 4, no. 3, pp. 1255–1261, Dec. 2022, doi: 10.47065/bits.v4i3.2288.

A. Aytekin, “DETERMINING CRITERIA WEIGHTS FOR VEHICLE TRACKING SYSTEM SELECTION USING PIPRECIA-S,” J. Process Manag. new Technol., vol. 10, no. 1–2, pp. 115–124, Jun. 2022, doi: 10.5937/jpmnt10-38145.

C. Meske and E. Bunde, “Design Principles for User Interfaces in AI-Based Decision Support Systems: The Case of Explainable Hate Speech Detection,” Inf. Syst. Front., vol. 25, no. 2, pp. 743–773, Mar. 2022, doi: 10.1007/s10796-021-10234-5.

A. H. Bademlioglu, A. S. Canbolat, and O. Kaynakli, “Multi-objective optimization of parameters affecting Organic Rankine Cycle performance characteristics with Taguchi-Grey Relational Analysis,” Renew. Sustain. Energy Rev., vol. 117, p. 109483, Jan. 2020, doi: 10.1016/j.rser.2019.109483.

H. Lu, Y. Zhao, X. Zhou, and Z. Wei, “Selection of Agricultural Machinery Based on Improved CRITIC-Entropy Weight and GRA-TOPSIS Method,” Processes, vol. 10, no. 2, p. 266, Jan. 2022, doi: 10.3390/pr10020266.

K. Mausam, A. Pare, S. K. Ghosh, and A. K. Tiwari, “Thermal performance analysis of hybrid-nanofluid based flat plate collector using Grey relational analysis (GRA): An approach for sustainable energy harvesting,” Therm. Sci. Eng. Prog., vol. 37, p. 101609, 2023.

M. O. Esangbedo, J. Xue, S. Bai, and C. O. Esangbedo, “Relaxed Rank Order Centroid Weighting MCDM Method With Improved Grey Relational Analysis for Subcontractor Selection: Photothermal Power Station Construction,” IEEE Trans. Eng. Manag., 2022, doi: 10.1109/TEM.2022.3204629.

S. A. Javed, A. Gunasekaran, and A. Mahmoudi, “DGRA: Multi-sourcing and supplier classification through Dynamic Grey Relational Analysis method,” Comput. Ind. Eng., vol. 173, p. 108674, Nov. 2022, doi: 10.1016/j.cie.2022.108674.

I. Oktaria, “Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Order Centroid (ROC) dalam Pemilihan Kegiatan Ekstrakulikuler,” J. Ilm. Inform. dan Ilmu Komput., vol. 2, no. 1, pp. 1–11, Mar. 2023, doi: 10.58602/jima-ilkom.v2i1.12.

A. Karim, S. Esabella, K. Kusmanto, M. Mesran, and U. Hasanah, “Analisa Penerapan Metode Operational Competitiveness Rating Analysis (OCRA) dan Metode Multi Attribute Utility Theory (MAUT) Dalam Pemilihan Calon Karyawan Tetap Menerapkan Pembobotan Rank Order Centroid (ROC),” J. MEDIA Inform. BUDIDARMA, vol. 5, no. 4, p. 1674, Oct. 2021, doi: 10.30865/mib.v5i4.3265.

A. Ozdagoglu, G. Zeynep Oztas, M. Kemal Keles, and V. Genc, “A comparative bus selection for intercity transportation with an integrated PIPRECIA & COPRAS-G,” Case Stud. Transp. Policy, vol. 10, no. 2, pp. 993–1004, 2022, doi: https://doi.org/10.1016/j.cstp.2022.03.012.

M. Yusuf, “Sistem Pendukung Keputusan Untuk Menentukan Pelanggan Terbaik Pada Pizza Oei-Oei Medan Menggunakan Metode SAW,” J. Ilmu Komput. Dan Sist. Inf., vol. 4, no. 2, pp. 51–58, 2021, doi: 10.9767/jikomsi.v4i2.142.

V. M. M. Siregar, S. Sonang, and E. Damanik, “SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PELANGGAN TERBAIK MENGGUNAKAN METODE WEIGHTED PRODUCT,” J. Tekinkom (Teknik Inf. dan Komputer), vol. 4, no. 2, pp. 239–244, 2021.

A. Prabowo and M. Iqbal, “Analisis Data Report Online Menggunakan Analytical Hierarchy Process dalam Pemilihan Pelanggan Terbaik,” J. Ilm. Komputasi, vol. 21, no. 3, pp. 355–362, Sep. 2022, doi: 10.32409/jikstik.21.3.3005.

A. F. O. Pasaribu and N. Nuroji, “Sistem Pendukung Keputusan Penentuan Pelanggan Terbaik Menggunakan Profile Matching,” J. Data Sci. Inf. Syst., vol. 1, no. 1, pp. 24–31, Feb. 2023, doi: 10.58602/dimis.v1i1.16.

H. Sulistiani, Setiawansyah, P. Palupiningsih, F. Hamidy, P. L. Sari, and Y. Khairunnisa, “Employee Performance Evaluation Using Multi-Attribute Utility Theory (MAUT) with PIPRECIA-S Weighting: A Case Study in Education Institution,” in 2023 International Conference on Informatics, Multimedia, Cyber and Informations System (ICIMCIS), 2023, pp. 369–373. doi: 10.1109/ICIMCIS60089.2023.10349017.

E. R. Susanto, A. Savitri Puspaningrum, and Z. Abidin, “Recommendations of Cash Social Assistance (BST) Recipients for People Affected by Covid-19 Using AHP-TOPSIS,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), Aug. 2023, pp. 190–195. doi: 10.1109/IConNECT56593.2023.10326776.

Setiawansyah, A. A. Aldino, P. Palupiningsih, G. F. Laxmi, E. D. Mega, and I. Septiana, “Determining Best Graduates Using TOPSIS with Surrogate Weighting Procedures Approach,” in 2023 International Conference on Networking, Electrical Engineering, Computer Science, and Technology (IConNECT), 2023, pp. 60–64. doi: 10.1109/IConNECT56593.2023.10327119.




DOI: http://dx.doi.org/10.61944/bids.v3i1.84

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Muhammad Waqas Arshad, Yuri Rahmanto, Setiawansyah Setiawansyah

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Bulletin of Informatics and Data Science
Asosiasi Peneliti Data Science Indonesia
Email: pdsi.bids@gmail.com
This work is licensed under a Creative Commons Attribution 4.0 International License.