Application of the Fuzzy Analysis Hierarchy Process to Develop AUN-QA
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Abstract
This study aimed to apply the Fuzzy Analytic Hierarchy Process (FAHP) to determine the weights of the AUN-QA criteria, thereby enhancing accuracy and reducing ambiguity in internal quality assessment scoring. The resulting FAHP-based weights were compared with the original faculty assessment scores to calculate the Absolute Percentage Error (APE). The study involved 17 quality assurance experts from Sripatum University, who conducted pairwise comparisons and consistency ratio analyses to derive the weights. The findings indicated that “Expected Learning Outcomes” and “Teaching and Learning Approach” received the highest weights, underscoring their crucial role in academic quality management and alignment with institutional missions. The APE values for the Faculty of Engineering and the Faculty of Information Technology were 1.563% and 2.344%, respectively, both below the 3% threshold, which confirms the model’s accuracy and robustness. Overall, the results demonstrate that the FAHP approach strengthens the credibility of internal quality assessment systems and provides a strategic decision-support tool for guiding curriculum development, faculty capacity building, and continuous quality improvement in higher education.
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