THE USE OF THE AHP AND TOPSIS METHODS IN ANALYZING THE SELECTION OF THE BEST CRYPTO (CASE STUDY: BITCOIN AND SOLANA)

Abstract

The development of digital financial technology has introduced a variety of crypto assets with different characteristics and mechanisms, necessitating an objective analytical approach to determine the most optimal asset. This research aims to identify the best crypto between Bitcoin and Solana by considering five main criteria: transaction speed, transaction cost, energy consumption, network security, and network stability. The approach used is descriptive quantitative with the application of the Analytic Hierarchy Process (AHP) method to determine the weight of each criterion and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives based on the obtained weights. Data was collected through a literature review and official sources from each crypto platform to ensure the validity and reliability of the results. Based on the analysis, Solana obtained the highest preference value as it showed significant superiority in transaction speed, cost efficiency, and low energy consumption, while Bitcoin remains superior in the aspect of more assured network security and stability. The combination of the AHP and TOPSIS methods proved capable of producing a systematic, rational, and measurable multi-criteria decision-making process. The results of this study have implications for the development of a data-driven digital asset evaluation model, which can serve as a reference for investors, market analysts, and researchers in conducting comparative assessments of crypto asset performance more efficiently, transparently, and based on empirical evidence, in line with the increasing need for analytical instruments in modern financial technology investment.