Author
Listed:
- Richard M. Pabelona Jr.
(College of Industrial Technology, Carlos Hilado Memorial State University)
- Crist Joseph G. Sermonia
(College of Industrial Technology, Carlos Hilado Memorial State University)
Abstract
The study aimed to design and develop a Cloud-based Inventory System with Quick Response (QR) Tagging for Technology Workshop to manage inventory system technology workshop. Specifically, the study aimed to design and develop a cloud-based inventory system with QR tagging with the technical features: managed equipment and user data, accurate printed QR code, real-time QR code scanning for equipment, actual monitoring of reports, mobile applications with internet-synchronization. The study also aimed to test the functionality of the aforementioned technical features, evaluate the usability of the system in terms of system usefulness, information quality, interface quality, and overall usability and to develop a user’s manual of the system. The method of research used was developmental and descriptive. Test cases were conducted to evaluate the identified technical features of the system. Post-Study System Usability Questionnaire (PSSUQ) a standardized research instrument was used to evaluate the system’s usability. Result of the study revealed that the system’s technical features has passed all test cases conducted. The usability of the system revealed that the system usefulness, information quality, interface quality, and overall usability were rated strongly agree. The user’s manual will guide its target users to use the system effectively. The system can be used on workshops both in school and industry to make the inventory system fast, accurate and convenient with QR technology.
Suggested Citation
Richard M. Pabelona Jr. & Crist Joseph G. Sermonia, 2025.
"Cloud-Based Inventory System with Quick Response (QR) Tagging for Technology Workshop,"
International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 12(1), pages 803-822, January.
Handle:
RePEc:bjc:journl:v:12:y:2025:i:1:p:803-822
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