Sistem Pendukung Keputusan Pemilihan Pelanggan Terbaik Menggunakan Metode SD-MOORA

Yuri Rahmanto

doi:10.58602/jaiti.v2i3.135

Yuri Rahmanto Universitas Teknokrat Indonesia

DOI: https://doi.org/10.58602/jaiti.v2i3.135

Keywords: Customer, Election, Ranking, SD-MOORA, DSS

Abstract

Selecting the best customer is an important process in business that aims to recognize high-value customers for the company based on factors such as purchase frequency, transaction value, loyalty, and long-term business potential. However, this process often faces challenges, especially when it comes to objective and consistent measurements. One of the main problems is the complex and dynamic variation of customer data, making it difficult for companies to determine the right metrics to comprehensively assess customers. SPK for selecting the best customers using the SD-MOORA method is a system designed to assist companies in evaluating and selecting the best customers based on various criteria. With the SD-MOORA method, the system can automatically consider changes in data or variability between criteria, making the evaluation process more dynamic and adaptive to data fluctuations. The results of the ranking of the best customers using the SD-MOORA method, Customer 8 occupies the first position with the highest optimization value of 0.39079, followed by Customer 4 who obtained a score of 0.3734. Furthermore, Customer 2 is in third place with a value of 0.35515. These results show that Customer 8 is the best based on optimization value, while Customer 5 is ranked at the bottom.

Downloads

Download data is not yet available.

References

R. Mugiarso, “PENENTUAN PERINGKAT PELANGGAN TERBAIK MENGGUNAKAN METODE RANK ORDER CENTROID DAN WEIGHTED PRODUCT (STUDI KASUS ONESNET),” Aisyah J. Informatics Electr. Eng., vol. 5, no. 2, pp. 135–140, 2023.

A. Raynaldi, A. Ikhwan, and M. D. Irawan, “Implementasi AHP Dan Promethee Dalam Pemilihan Bengkel Resmi Terbaik Di Deli Serdang,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 6, no. 2, p. 687, Jul. 2023, doi: 10.53513/jsk.v6i2.8363.

R. T. Aldisa, “Sistem Pendukung Keputusan Pemilihan Barista Coffee Terbaik Menerapkan Metode Multi Objective Optimization on The Basis of Ratio Analysis (MOORA) dan ROC,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 3, no. 6, pp. 1022–1030, 2023, doi: 10.30865/klik.v3i6.959.

A. Purnamawati, M. N. Winarto, and D. U. E. Saputri, “Sistem Pendukung Keputusan Penentuan Produk Terbaik Menggunakan Metode Preference Selection Index,” Chain J. Comput. Technol. Comput. Eng. Informatics, vol. 1, no. 2, pp. 56–67, 2023.

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.

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.

H. Sulistiani, S. Setiawansyah, A. F. O. Pasaribu, P. Palupiningsih, K. Anwar, and V. H. Saputra, “New TOPSIS: Modification of the TOPSIS Method for Objective Determination of Weighting,” Int. J. Intell. Eng. Syst., vol. 17, no. 5, pp. 991–1003, Oct. 2024, doi: 10.22266/ijies2024.1031.74.

S. Setiawansyah, S. H. Hadad, A. A. Aldino, P. Palupiningsih, G. Fitri Laxmi, and D. A. Megawaty, “Employing PIPRECIA-S weighting with MABAC: a strategy for identifying organizational leadership elections,” Bull. Electr. Eng. Informatics, vol. 13, no. 6, pp. 4273–4284, Dec. 2024, doi: 10.11591/eei.v13i6.7713.

M. W. Arshad, S. Sintaro, Y. Rahmanto, A. Wantoro, and S. Setiawansyah, “Optimization of Alternative Assessment with Modified MOORA Method: Case Study of Contract Employee Selection,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 6, pp. 3099–3107, 2024, doi: 10.30865/klik.v4i6.1891.

B. Zhang, P. Niu, X. Guo, and J. He, “Fuzzy PID control of permanent magnet synchronous motor electric steering engine by improved beetle antennae search algorithm,” Sci. Rep., vol. 14, no. 1, p. 2898, 2024, doi: 10.1038/s41598-024-52600-8.

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.

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.

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, 2023.

S. Setiawansyah, P. Parjito, D. A. Megawaty, N. Nuralia, and Y. Rahmanto, “Implementation of The Framework for The Application of System Thinking for School Financial Information Systems,” Tech-E, vol. 5, no. 1, pp. 1–10, 2021.

A. D. Christiana and E. Mailoa, “Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Berbasis Website dengan Menggunakan Metode TOPSIS,” AITI, vol. 19, no. 1 SE-Articles, pp. 31–47, Jul. 2022, doi: 10.24246/aiti.v19i1.31-47.

A. F. Pasaribu, A. Surahman, A. T. Priandika, S. Sintaro, and Y. T. Utami, “Sistem Pendukung Keputusan Seleksi Penerimaan Guru Menggunakan SAW,” J. Artif. Intell. Technol. Inf., vol. 1, no. 1, pp. 13–19, Feb. 2023, doi: 10.58602/jaiti.v1i1.21.

F. J. Mahendra and S. Setiawansyah, “Sistem Pendukung Keputusan Penilaian Kinerja Tenaga Honor Panitia Pengawas Menggunakan Kombinasi Logarithmic Least Squares Weighting dan MABAC,” J. Comput. Syst. Informatics, vol. 5, no. 3, pp. 636–647, 2024, doi: 10.47065/josyc.v5i3.5158.