Journal of Computer System and Informatics (JoSYC)
Vol 6 No 3 (2025): May 2025

Hybrid G2M Weighting and WASPAS Method for Business Partner Selection: A Decision Support Approach

Wang, Junhai (Unknown)
Setiawansyah, Setiawansyah (Unknown)
Alita, Debby (Unknown)



Article Info

Publish Date
31 May 2025

Abstract

Choosing the right business partner is a crucial factor in the success and continuity of a company's operations. The main issue in selecting business partners is the complexity of balancing various interconnected and often conflicting factors. Another problem lies in the subjectivity and limitations of information. Evaluators or decision-makers may have differing views on the priority of criteria or the interpretation of the available data. This study proposes a hybrid method-based decision support system approach that combines G2M Weighting and WASPAS to address the challenges in complex and uncertain multi-criteria evaluations. The G2M method is used to objectively determine the weight of criteria based on geometric averages in gray environments, so as to be able to capture data variability and uncertainty. Furthermore, the WASPAS method is applied to calculate the final value and rank the alternative business partners based on a combination of additive and multiplicative approaches. The ranking chart for business partner selection using the G2M Weighting and WASPAS method shows that Partner G gets the highest score of 9.93E+03, followed by Partner A and Partner E who have the same score of 9.43E+03. Meanwhile, Partner D had the lowest score, which was 5.97E+03. This ranking of business partner selection shows that Partner G is the best choice as a business partner based on the evaluation method used. The results of the study show that this hybrid approach provides more accurate, stable, and comprehensive evaluation results than conventional methods. This approach can be an effective solution for companies in supporting the strategic decision-making process in choosing the best business partners.

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Journal Info

Abbrev

josyc

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

Description

Journal of Computer System and Informatics (JoSYC) covers the whole spectrum of Artificial Inteligent, Computer System, Informatics Technique which includes, but is not limited to: Soft Computing, Distributed Intelligent Systems, Database Management and Information Retrieval, Evolutionary ...