Kombinasi Metode Rank Sum dan Grey Relational Analysis dalam Pemilihan Pelanggan Terbaik

I Wayan Sriyasa

doi:10.58602/itsecs.v2i4.162

I Wayan Sriyasa Universitas Pakuan

DOI: https://doi.org/10.58602/itsecs.v2i4.162

Keywords: Alternative, GRA, Combination, Best Customer, Rank Sum

Abstract

Selecting the best customers is an important process in marketing and customer relationship management (CRM) strategies that aim to identify the customers who contribute the most to the success of the business. The main problem in selecting the best customer lies in the difficulty in objectively assessing and comparing customer performance, given the diversity of characteristics of each customer. The combination of rank sum and GRA methods is an approach that combines two powerful techniques in multi-attribute decision-making to evaluate and select the best alternatives. This approach aims to overcome the limitations of each method when used separately, and take advantage of the advantages of both methods in producing more objective and accurate decisions. The results of the alternative ranking show that Customer C is ranked first with a value of 0.2, followed by Customer A (0.1865) and Customer G (0.1864). Meanwhile, customers with the lowest GHG values, such as Customer H (0.0167), are in last position because their performance is furthest from ideal conditions. These results help visualize the ranking order based on the performance of each alternative, making it easier to make decisions in choosing the best customers. This research contributes to generating objective and transparent decisions, as well as helping companies identify potential customers based on criteria such as loyalty, revenue contribution, or long-term potential.

References

M. Ardianto and R. Rusliyawati, “Sistem Pendukung Keputusan Pemilihan Pelanggan Terbaik Menggunakan Metode Multi-Objective Optimization on the basis of Ratio Analysis dan Pembobotan Entropy,” J. Inf. Syst. Res., vol. 5, no. 4, pp. 1261–1270, 2024, doi: 10.47065/josh.v5i4.5527.

M. Y. Safii and E. Ardhianto, “Sistem Pendukung Keputusan dalam Pemilihan Sales Marketing Terbaik Menggunakan Simple Additive Weighting (SAW) Berbasis Website (Studi Kasus: PT. Citra Swarna Group (CSG),” J. JTIK (Jurnal Teknol. Inf. dan Komunikasi), vol. 8, no. 1, pp. 137–144, Jan. 2024, doi: 10.35870/jtik.v8i1.1358.

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.

R. Andika, “Kombinasi Grey Relational Analysis (GRA) dan ROC Dalam Penentuan Promosi Jabatan Supervisor,” Chain J. Comput. Technol. Comput. Eng. Informatics, vol. 2, no. 1, pp. 37–44, 2024, doi: 10.58602/chain.v2i1.94.

S. Sintaro, “Penerapan Metode Grey Relational Analysis (GRA) Dalam Pemilihan E-Commerce,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 1, no. 4, pp. 166–173, 2023, doi: 10.58602/itsecs.v1i4.75.

A. A. Izka and H. Sulistiani, “Penerapan Metode Pembobotan LOPCOW dan Grey Relational Analysis Dalam Penentuan Pemasok Toserba Terbaik,” J. Inf. Syst. Res., vol. 5, no. 4, pp. 1352–1360, 2024, doi: 10.47065/josh.v5i4.5537.

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.

B. S. Nithyananda, G. V Naveen Prakash, N. Ankegowda, K. B. Vinay, and A. Anand, “Optimization of Performance and Emission Responses of Common Rail Direct Injection Engine by Taguchi-Grey Relational Analysis Technique,” in RAiSE-2023, Jan. 2024, vol. 59, no. 1, p. 140. doi: 10.3390/engproc2023059140.

W. Saputra, S. A. Wardana, H. Wahyuda, and D. A. Megawaty, “Penerapan Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Sum Dalam Pemilihan Siswa Terbaik,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 2, no. 1, pp. 12–21, 2024.

S. Sintaro, “Sistem Pendukung Keputusan Penentuan Barista Terbaik Menggunakan Rank Sum dan Additive Ratio Assessment (ARAS),” J. Ilm. Comput. Sci., vol. 2, no. 1, pp. 39–49, 2023, doi: 10.58602/jics.v2i1.15.

I. M. Hezam, A. K. Mishra, D. Pamucar, P. Rani, and A. R. Mishra, “Standard deviation and rank sum-based MARCOS model under intuitionistic fuzzy information for hospital site selection,” Kybernetes, 2023.

Y. P. Soni and E. Fernandez, “Multi-Criteria Rank-Based Planning of the Distribution System with HOMER Integrated Weighted Sum Model,” in 2022 IEEE 10th Power India International Conference (PIICON), Nov. 2022, pp. 1–5. doi: 10.1109/PIICON56320.2022.10045163.

P. Citra, I. W. Sriyasa, and H. B. Santoso, “Sistem Pendukung Keputusan Penentuan Kinerja Sales Terbaik Menggunakan Kombinasi Grey Relational Analysis dan Pembobotan Rank Sum,” J. Ilm. Comput. Sci., vol. 2, no. 2, pp. 99–108, Jan. 2024, doi: 10.58602/jics.v2i2.26.

S. Setiawansyah, “IT Personnel Recruitment Decision Support System: Combination of TOPSIS and Entropy Weighting Methods,” J. Artif. Intell. Technol. Inf., vol. 2, no. 3 SE-Articles, pp. 118–130, Sep. 2024, doi: 10.58602/jaiti.v2i3.131.

E. Gusbriana and H. Sulistiani, “Sistem Informasi Management Persediaan Barang Menggunakan Metode Moving Average Cost Method,” J. Inf. Technol. Softw. Eng. Comput. Sci., vol. 1, no. 4, pp. 174–182, 2023.