Optimizing E-Commerce Platform Selection Using Root Assessment Method and MEREC Weighting

Junhai Wang; Dedi Darwis; Rakhmat Dedi  Gunawan; Fenty Ariany

doi:10.33365/jatika.v6i1.6

Junhai Wang Zhejiang Technical Institute of Economics
Dedi Darwis Universitas Teknokrat Indonesia
Rakhmat Dedi Gunawan Universitas Teknokrat Indonesia
Fenty Ariany Universitas Teknokrat Indonesia

DOI: https://doi.org/10.33365/jatika.v6i1.6

Keywords: E-commerce platforms, Decision-making, Root assessment method, MEREC weighting, Objective approach

Abstract

The number of users of e-commerce platforms has increased significantly in recent years, and consumers are now more likely to shop online due to ease of access, diverse product choices, and flexibility in transaction times. The difficulty in determining the best e-commerce platform is often caused by subjectivity in the weighting of the criteria used for evaluation. The weighting process is carried out based on the preferences of certain individuals or groups, without considering objective data. This research aims to apply an objective, structured, and accurate approach in evaluating and ranking e-commerce platforms based on relevant multi-dimensional criteria. By using the root assessment method, the evaluation process can be carried out systematically through hierarchical analysis, while the MEREC weighting ensures that the weight of each criterion reflects its real impact on the outcome of the decision. Through the combination of these two methods, this research is expected to make a significant contribution to improving the quality of decision-making, especially in helping users or business people choose the e-commerce platform that best suits their needs. The results of the final score calculation Platform E was ranked first with the highest score of 4.87083, Platform A was ranked second with a score of 4.85162, and Platform B was ranked third with a score of 4.83842. Future research should address the identified limitations by exploring the integration of advanced predictive analytics and artificial intelligence techniques to improve the adaptability and resilience of models. In addition, sensitivity analysis of the MEREC Root Assessment and Weighting Methods should be performed to understand its performance under various data conditions.

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