INTEGRATED APPLICATION OF MABAC, CODAS AND ARAS METHODS IN ASSESSING THE RELIABILITY OF INFORMATION SYSTEMS
DOI:
https://doi.org/10.37943/23GTAR2557Keywords:
information systems, reliability, multicriteria analysis, MABAC method, CODAS method, ARAS method, comparative analysisAbstract
In the modern digital world, the reliability of information systems has become one of the most important factors that determine the stability and efficiency of organizations. Even short-term system failures can cause serious financial losses, data breaches, and reputational damage. Therefore, assessing and improving the reliability of information systems is an essential part of ensuring their overall quality and resilience. To achieve an objective and comprehensive evaluation, this study applies multi-criteria decision-making (MCDM) methods that take into account both technical and organizational factors. The main focus is on the ARAS (Additive Ratio Assessment) method, which not only ranks the studied systems but also expresses the reliability level in percentage form. This makes the results clear, comparable, and easy to interpret in practice. For additional verification and comparison, the MABAC and CODAS methods were used. They help confirm the stability of rankings and support the validity of the conclusions drawn from the ARAS method. The selection of assessment criteria was based on the international standard ISO/IEC 25010:2023, which defines the quality model for software and information systems. Expert evaluations were carried out across ten characteristics — functionality, performance, compatibility, usability, reliability, security, maintainability, portability, recoverability, and adaptability. Using this data, all three MCDM methods were applied to calculate and compare the reliability of selected systems. The results show that ARAS provides a clear quantitative measure of reliability, while MABAC and CODAS strengthen the analysis by verifying ranking consistency. The combination of these approaches offers a practical and reliable framework for evaluating the quality and dependability of modern information systems.
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