Decision Support System for Platform Selection in E-Commerce Using the OWH-TOPSIS Method


  • Junhai Wang Zhejiang Technical Institute of Economics, Zhejiang, China
  • Auliya Rahman Isnain Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
  • Ryan Randy Suryono Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
  • Yuri Rahmanto Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
  • Mesran Mesran Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
  • Setiawansyah Setiawansyah * Mail Universitas Teknokrat Indonesia, Bandar Lampung, Indonesia
  • (*) Corresponding Author
Keywords: E-Commerce; Determining; Decision Support System; Platform; OWH-TOPSIS

Abstract

Platforms in e-commerce are digital systems that allow online transactions to buy and sell products or services. E-commerce platforms also provide benefits for business actors because they are able to reach a wider market without geographical restrictions, while offering efficiency in business operations. The main problem in choosing a platform for e-commerce is often related to the sheer number of options available and the variety of criteria that must be considered. Criteria such as fees, platform popularity, transaction security, ease of use, features provided, as well as customer service support are important factors in determining the most suitable platform. The implementation of a decision support system to help select the optimal e-commerce platform by applying the OWH-TOPSIS method shows that this system can provide accurate and effective recommendations, so that it can be used as a reference for users in determining the e-commerce platform that suits their needs. The decision support system using the OWH-TOPSIS method provides an efficient and objective solution in the selection of e-commerce platforms. The results of the ranking of the best e-commerce platforms show that Platform D occupies the top position with the highest score value, which is 0.882. In second place is Platform E which obtained a score of 0.8599, followed by Platform A with a score of 0.8341.

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Article History
Submitted: 2024-09-29
Published: 2024-11-26
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