Analysis of Finance Risk with Clustering Algorithm Using VIKOR Method

This paper proposes a new approach to business valuation that considers financial and non-financial weights, taking into account both drivers and simultaneous installation of many MCDMs (many criteria decision-making) methods. The case study selected the world's leading road freight companies to determine the weight of the drivers and compare the companies using various methods. Unpredictability, performance, and innovation were the three subjective interesting measurements used to evaluate patterns. This paper proposes a hybrid interval type-2 ambiguous multi-dimensional decision-making model that utilizes the VIKOR method to solve problems with conflicting and random criteria and different units. The system created aims to find a compromise solution to the conflict that is acceptable to the decision-maker assuming that they want a closer solution and are willing to evaluate more alternatives. In this paper, linguistic values are used to evaluate and weigh the established criteria. The proposed model uses vague set theory and VIKOR to create a step-by-step multi-criteria decision-making (MCDM) model. A numerical example was provided to illustrate the application of the proposed model using various methods alternatives as clustering algorithms, financial risk analysis, Data Envelopment Analysis (DEA), and VIKOR for all implication parameters. From the results, COBWEB ranks first, whereas Graphpartitioning ranks the lowest.