Multi-Criteria Decision Model for Ranking the Best Marketplace Using CRISUS Weighting and OPARA Ranking

Akil  Thalib; Ayuni  Asistyasari; Yosep Nuryaman; Raditya Rimbawan  Oprasto; Aditia Yudhistira

doi:10.33365/jatika.v7i1.1568

Akil Thalib Institut Teknologi Gamalama
Ayuni Asistyasari Universitas Bina Sarana Informatika
Yosep Nuryaman Universitas Bina Sarana Informatika
Raditya Rimbawan Oprasto Universitas Buddhi Dharma
Aditia Yudhistira Universitas Teknokrat Indonesia

DOI: https://doi.org/10.33365/jatika.v7i1.1568

Keywords: Multi-Criteria Decision Making (MCDM), CRISUS Weighting, OPARA Method, Marketplace Ranking, Decision Support System (DSS)

Abstract

The rapid growth of e-commerce marketplaces in Indonesia has increased competition among platforms and created challenges in identifying the most suitable marketplace for users and businesses. Previous studies commonly applied conventional Multi-Criteria Decision-Making (MCDM) approaches, yet many of these methods rely heavily on subjective weighting or limited data-based evaluation, which may lead to inconsistent ranking results. Therefore, this study aims to develop a more objective decision-making model for marketplace evaluation by integrating the CRISUS weighting method with the OPARA ranking approach. The dataset consists of quantitative marketplace performance indicators collected from public digital statistics, including monthly visits, annual visits, application ratings, number of downloads, and the number of active sellers for several major marketplaces operating in Indonesia. The CRISUS method is used to determine criterion weights based on actual data variation to reduce subjective bias, while OPARA evaluates the alternatives through an optimized pairwise ratio mechanism to obtain the final preference values. The experimental results indicate that Shopee achieves the highest score of 0.3078, followed by Lazada with 0.2476 and Tokopedia with 0.2327, demonstrating their stronger performance compared with other marketplace alternatives based on the evaluated criteria. These findings contribute both academically and practically by providing a transparent and data-driven MCDM framework that improves the reliability of marketplace ranking and can support stakeholders in making more informed platform selection decisions.

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