Selection of Asset Identification Technology for University Asset Logistics Management Using Fuzzy AHP

Yovita Yulia M. Zai; Refki Riyantori; Ade Putra Nanda

doi:10.63922/ijebir.v5i05.5685

Yovita Yulia M. Zai Faculty Member, Department of Logistics (Undergraduate Program) - Faculty of Social and Business, Universitas Mercubaktijaya, Padang – Indonesia
Refki Riyantori Faculty Member, Department of Logistics (Undergraduate Program) - Faculty of Social and Business, Universitas Mercubaktijaya, Padang – Indonesia
Ade Putra Nanda Faculty Member, Department of Health Informatics (Undergraduate Program) - Faculty of Health and Sciences, Universitas Mercubaktijaya, Padang – Indonesia

DOI: https://doi.org/10.63922/ijebir.v5i05.5685

Keywords: Fuzzy Analytic Hierarchy Process (Fuzzy AHP), Asset Logistics Management, Asset Identification Technology, Radio Frequency Identification (RFID), Barcode

Abstract

Asset logistics management plays a critical role in enhancing operational efficiency, accountability, and decision-making in higher education institutions. Although Universitas Mercubaktijaya has developed an Asset Management Information System, the selection of the most appropriate asset identification technology to support its implementation has not been systematically evaluated. This study aims to identify the most suitable asset identification technology using a Multi-Criteria Decision-Making (MCDM) approach based on the Fuzzy Analytic Hierarchy Process (Fuzzy AHP). The study involved nine experts who evaluated three technology alternatives—Barcode, Radio Frequency Identification (RFID), and Hybrid RFID–Barcode—against eight decision criteria. The results indicate that asset identification accuracy is the most influential criterion, with a weight of 0.1956, followed by reading speed and system integration, each with a weight of 0.1800. The global ranking reveals that the Hybrid RFID–Barcode alternative achieves the highest priority weight (0.4052), followed by RFID (0.3240) and Barcode (0.2708). The findings demonstrate that the hybrid approach is the most suitable asset identification technology for supporting university asset logistics management. The novelty of this study lies in the development of a Fuzzy AHP-based decision-making model that integrates asset management, logistics, and asset identification technologies to support the digital transformation of asset logistics management in higher education institutions.

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