Implementation of a Decision Support System for Selecting the Best Clothing Brand Using the Website-Based TOPSIS Method
DOI:
https://doi.org/10.65897/jais.v1.i2.72Keywords:
decision support system, TOPSIS, clothing brand selection, multi-criteria, web-based systemAbstract
The rapid growth of the fashion market increases the number of available clothing brands, making it harder for consumers to select the best option under multiple criteria. This study develops a web-based decision support system for selecting the best clothing brand using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The criteria include price as a cost criterion and material quality, comfort, durability, and suitability as benefit criteria. Brand alternatives are evaluated on a 1–10 scale and processed through TOPSIS steps, including normalization, weighting, determining ideal solutions, computing distances to the positive and negative ideal solutions, and calculating the preference value (Ci). The ranking results indicate that Elizabeth (A6) achieves the highest preference score (Ci = 0.723779), thus recommended as the best brand. The proposed system supports criteria and alternative input, automated computation, transparent step-by-step calculations, and result export, enabling more objective and efficient decision-making.
References
[1] H. Hertyana et al., “Sistem Pendukung Keputusan Pemilihan Laptop Dengan Menggunakan Metode Topsis,” vol. 06, no. 02, pp. 36–44, 2021.
[2] K. Adra, M. Mahardi, N. C. Setiyono, and S. R. Wicaksono, “Analisis Pendukung Keputusan Pemilihan Investasi TI Menggunakan Metode TOPSIS ( Studi Kasus : Investasi Server ),” vol. 2, no. 1, pp. 71–78, 2022.
[3] H. Mustafidah and R. P. Mayasari, “Sistem Pendukung Keputusan Menggunakan Metode TOPSIS untuk Pemilihan Lembaga Bimbingan Belajar,” vol. 15, no. 1, pp. 39–53, 2018.
[4] H. W. P. Desi Andreswari, S.T., M.Cs., Ferzha Putra Utama, S.T., M.Eng., “SISTEM PENDUKUNG KEPUTUSAN SELEKSI PROPOSAL PROGRAM KREATIVTAS MAHASISWA MENGGUNAKAN METODE TOPSIS BERBASIS WEB,” 2021.
[5] A. Azhari and Hera Fransiska, “IMPLEMENTASI METODE TOPSIS PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KONSUMEN LOYALITAS,” vol. 2, no. 2, pp. 67–72, 2025.
[6] P. Jurusan, “Jurnal KomtekInfo Penerapan Metode TOPSIS pada Sistem Pendukung Keputusan,” vol. 11, no. 4, pp. 409–418, 2024.
[7] J. Sistem, S. Kasus, T. Keripik, R. Jaya, and B. Lampung, “Sistem Pendukung Keputusan Pemilihan Suplier Menggunakan Metode Topsis,” vol. 14, no. 1, pp. 87–93, 2023.
[8] F. Ramadhani and I. P. Sari, “InfoTekJar : Jurnal Nasional Implementasi Metode Topsis dalam Menangani Masalah Pengalokasian Dosen Pembimbing Skripsi dilingkungan Fakultas Ilmu Komputer dan Teknologi Informasi Universitas Muhammadiyah Sumatera Utara,” vol. 1, 2021.
[9] R. Y. R. I Wayan Aries Agetia1, Suraya2, “IMPLEMENTASI METODE TOPSIS PADA SPK PENENTUAN PENERIMA BEASISWA DI IST AKPRIND BERBASIS WEB,” pp. 20–28, 2020.
[10] D. R. Rahmalita, A. Mahmudi, and Y. A. Pranoto, “MENGGUNAKAN METODE TOPSIS ( STUDI KASUS : KOPERASI KEMBANG ARUM AYU ),” vol. 8, no. 2, pp. 1214–1220, 2024.
[11] H. Yen, V. S. Ponnambalam, D. C. Flanagan, C. S. Renschler, A. Srivastava, and M. R. Williams, “WEPP-COMPARE: A web-based decision support system for comprehensive land management and soil erosion assessment,” Environ. Model. Softw., vol. 193, p. 106643, Sep. 2025.
[12] H. Y. Joo and J. H. Moon, “Evaluating shelter suitability during nuclear accidents using the TOPSIS multi-criteria decision-making method,” Nucl. Eng. Technol., vol. 57, no. 9, p. 103648, Sep. 2025.
[13] T. J. Dilling, “Artificial Intelligence Research: The Utility and Design of a Relational Database System,” Adv. Radiat. Oncol., vol. 5, no. 6, pp. 1280–1285, Nov. 2020.
[14] A. V. Dong, C. Azzaro-Pantel, and M. Boix, “Multi-period optimal design of an aerospace CFRP waste management supply chain: Data set, variables and criteria for the development of a multi-objective MILP model,” Data Br., vol. 28, p. 104766, Feb. 2020.
[15] H. Gong, Q. Peng, L. Liu, and X. Yang, “A decision-making system for traffic management during large-scale road network construction,” Expert Syst. Appl., vol. 292, p. 128527, Nov. 2025.
[16] N. C. Wu et al., “Reporting guidelines for terrestrial respirometry: Building openness, transparency of metabolic rate and evaporative water loss data,” Comp. Biochem. Physiol. Part A Mol. Integr. Physiol., vol. 296, p. 111688, Oct. 2024.
[17] B. T. Stewart et al., “Optimizing the user-experience (UX) and −interface (UI) of a mHealth application to aid recovery from burn injury (BurnCORE) through a user-centered design approach,” Burn. Open, vol. 11, p. 100409, Jul. 2025.
[18] N. K. Dewberry et al., “A real-time VR-enabled digital twin framework for multi-user interaction in Industry 4.0,” Manuf. Lett., vol. 44, pp. 1486–1497, Aug. 2025.
[19] Z. Wu et al., “Development of a smartphone-integrated handheld automated biochemical analyzer for point-of-care testing of urinary albumin,” J. Pharm. Anal., vol. 15, no. 3, p. 101041, Mar. 2025.
[20] W. E. Donald, “Content analysis of metadata, titles, and abstracts (CAMTA): application of the method to business and management research,” Manag. Res. Rev., vol. 45, no. 1, pp. 47–64, Jan. 2022.
Downloads
Published
Issue
Section
License
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).
Under this license, users are permitted to copy, distribute, display, and perform the work, and to make derivative works, provided that appropriate credit is given to the author(s) and the source, and that any derivative works are distributed under the same license.
