Bulletin of Informatics and Data Science
Vol 3, No 2 (2024): November 2024

Selection of the Best E-Commerce Platform Based on User Ratings using a Combination Entropy and SAW Methods

Ulum, Faruk (Unknown)
Wang, Junhai (Unknown)
Setiawansyah, Setiawansyah (Unknown)
Aryanti, Riska (Unknown)



Article Info

Publish Date
20 Nov 2024

Abstract

Choosing the right e-commerce platform has a crucial role for consumers and business actors. For consumers, a reliable and user-friendly platform provides a safe, convenient, and efficient shopping experience. Considering various aspects of choosing the right e-commerce platform is a strategic investment that can provide long-term added value for all parties involved in the digital ecosystem. The purpose of this study is to identify and determine the best e-commerce platforms based on user experience and assessment with an objective and structured decision-making approach using a combination of Entropy and SAW methods. The results of the ranking of the best e-commerce platform selection determined through the combination of the Entropy and SAW methods, obtained that Shopee ranked first with the highest preference value of 0.9819, followed by Tokopedia in second place with a value of 0.973. Furthermore, Blibli is in third place with a score of 0.9401, followed by Lazada with a score of 0.9305, and the last is Bukalapak with a score of 0.9021. This research makes a significant contribution to multi-criteria decision-making by applying a combination of Entropy and SAW methods to evaluate and determine the best e-commerce platform based on user assessments. The results of this research can be used as a practical reference as a basis for strategic decision-making in choosing the e-commerce platform that best suits market needs

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Journal Info

Abbrev

bids

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering Engineering

Description

The Bulletin of Informatics and Data Science journal discusses studies in the fields of Informatics, DSS, AI, and ES, as a forum for expressing research results both conceptually and technically related to Data ...