A Weighted Product-Based Decision Support System for Multi-Criteria Selection of Imported Apparel Suppliers in a Small Boutique Retailer

Aldania Dwi Cahya; Raja Tama Andri Agus; Santoso

doi:10.56427/jcbd.v5i3.1052

Authors

Aldania Dwi Cahya Universitas Royal
Raja Tama Andri Agus Universitas Royal
Santoso Universitas Royal

DOI:

https://doi.org/10.56427/jcbd.v5i3.1052

Keywords:

Decision Support System, Weighted Product, Supplier Selection, Multi-Criteria Decision Making, Sensitivity Analysis

Abstract

Supplier selection determines product availability, quality, and cost structure in apparel retailing, yet micro-scale retailers commonly rely on the owner’s personal judgement, producing decisions that are subjective and difficult to audit. This study designs, implements, and validates a web-based decision support system that applies the Weighted Product method to rank imported apparel suppliers at Devincci Boutique, a micro retailer in North Sumatra, Indonesia. A quantitative case-study approach was used, with data obtained through structured interviews, direct observation, and a literature review. Ten suppliers were evaluated against five criteria: price (cost, 0.25), product quality (benefit, 0.25), delivery punctuality (benefit, 0.20), service (benefit, 0.15), and supplier distance (cost, 0.15), each rated on a five-point ordinal scale. The computation produced preference values ranging from 0.0717 to 0.1358, with Toko One K (A10) ranked first and Toko Mariacloset (A3) second (0.1186). A sensitivity analysis across eleven weight scenarios left the top-ranked alternative unchanged, and cross-validation against Simple Additive Weighting yielded a Spearman rank correlation of 0.976. All twelve black box test scenarios passed, and system output reproduced the manual computation to four decimal places. The study contributes a replicable and stability-tested supplier selection procedure for micro-scale imported fashion retailing.

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References

[1] S. Chakraborty, R. D. Raut, T. M. Rofin, and S. Chakraborty, “Supplier Selection Using Multi-Criteria Decision Making Methods: a Somprehensive Review,” OPSEARCH, Sep. 2025, doi: 10.1007/s12597-025-01009-6.

[2] J. Fang, W. Zhou, and L. Xiong, “Multi-Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Digital Supply Chain Resilience,” Ann. Oper. Res., Dec. 2024, doi: 10.1007/s10479-024-06435-1.

[3] A. Karabayir and A. R. Botsali, “Supplier Selection Among Different Scale Construction Companies Using Fuzzy AHP and FUZZY TOPSIS,” El-Cezeri Fen ve Mühendislik Derg., Dec. 2021, doi: 10.31202/ecjse.933617.

[4] D. Rivaldi, F. Pulansari, and A. P. Kartika, “Analysis of Bolt Supplier Selection Using AHP-TOPSIS and Fuzzy-AHP Method Comparison (PT Stechoq Robotika Indonesia),” Mak. J. Manaj., vol. 9, no. 2, pp. 147–165, Dec. 2023, doi: 10.37403/mjm.v9i2.569.

[5] Jovanica and E. Dazki, “Komparasi Metode Simple Additive Weighting (SAW) dengan Weighted Product (WP) untuk Penilaian Tenaga Kerja Indonesia,” JSiI (Jurnal Sist. Informasi), vol. 9, no. 2, pp. 132–140, Sep. 2022, doi: 10.30656/jsii.v9i2.5066.

[6] W. Hadikurniawati, E. Winarno, T. D. Cahyono, and D. Abdullah, “Comparison of AHP-TOPSIS Hybrid Methods, WP and SAW for Multi-Attribute Decision-Making to Select the Best Electrical Expert,” Dec. 07, 2018, Institute of Physics Publishing. doi: 10.1088/1742-6596/1114/1/012100.

[7] M. A. Puspa, M. Lasena, H. Husain, and Z. Sidik, “Implementasi Metode Weighted Product Dalam Pengambilan keputusan Penilaian Kinerja Karyawan,” Bull. Inf. Technol., vol. 4, no. 4, pp. 439–447, Dec. 2023, doi: 10.47065/bit.v4i4.991.

[8] R. Supardi and A. Sudarsono, “Penerapan Metode Weighted Product (WP) Dalam Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Pada PT. Agrodehasen Bengkulu,” J. MEDIA INFOTAMA, vol. 19, no. 1, pp. 141–147, Apr. 2023, doi: 10.37676/jmi.v19i1.3505.

[9] N. M. Y. D. Rahayu and N. P. D. E. Yanti, “Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Bagi Usaha Mikro Kecil Menengah (UMKM) dengan Metode Weighted Product (WP),” J. Teknol. Inf. dan Komput., vol. 10, no. 4, Jan. 2025, doi: 10.36002/jutik.v10i4.3711.

[10] S. W. Nduru and H. Lubis, “Decision Support System For Selection Of Drug Supplier With Weighted Product Method,” J. ICT Inf. Commun. Technol., vol. 13, no. 1, pp. 12–19, Apr. 2022, doi: 10.35335/jict.v13i1.33.

[11] D. Fanita and B. Sinaga, “Supplier Selection Decision Support System Drug Wighted Methods Product (WP),” Journal of Computer Networks, Architecture and High Performance Computing., vol. 2, no. 2, pp. 135-139, Jan. 2020. [Online]. Available:https://garuda.kemdiktisaintek.go.id/documents/detail/1830303

[12] R. Serpus, A. K. Alexander, C. M. Uscha, and D. hajar, “Evaluation of Wood Supplier Selection Using the Weighted Product and TOPSIS Methods at CV Bela Sejahtera,” Median. Indones. J. Creat. Bus. Technol., vol. 2, no. 1, pp. 48–58, Jul. 2026, doi: 10.64425/4p1jyz02.

[13] M. A. F. Sihotang, Fadlisyah, and Fajriana, “Sistem Pendukung Keputusan Pemilihan Framework Web Menggunakan Metode Weighted Product,” Rabit J. Teknol. dan Sist. Inf. Univrab, vol. 11, no. 1, pp. 41–57, Jan. 2026, doi: 10.36341/rabit.v11i1.6610.

[14] A. Pujiastuti, A. Kusumaningrum, and M. A. Sofyan, “Web-based decision support system for guest star determination in e-marketplace using Weighted Product method,” Compiler, vol. 9, no. 2, p. 109, Dec. 2020, doi: 10.28989/compiler.v9i2.824.

[15] A. P. Kusuma, “Analysis Implementation Analytical Hierarchy Process Method and Weighted Product for Ranking Internet Package Selection System,” Procedia Eng. Life Sci., vol. 2, no.1 Dec. 2021, doi: 10.21070/pels.v2i0.1173.

[16] Z. S. Zulkifli and N. Zamri, “Conceptual Framework for Designing an Expert Advisor System Based on Technical Indicators: Evidence from Malaysian Forex Traders,” J. Comput. Digit. Bus., vol. 5, no. 1, pp. 6–9, Jan. 2026, doi: 10.56427/jcbd.v5i1.793.