Development of PRIMA as a Smart Data Hub Platform for Quality Assurance System Integration in Vocational Higher Education

Abstract

Digitization of quality assurance and accreditation is a strategic necessity for universities to improve data management efficiency and support accurate, information-based decision-making. This research focuses on the design of PRIMA PPMPP as a Smart Data Hub Platform capable of integrating accreditation data and monitoring the quality of learning at the Manado State Polytechnic. The research methodology includes needs analysis, system architecture design, data modeling and information flow, user-centered interface design, and design validation through expert review. The results show that the multi-layer architecture design developed—including the data source layer, data integration layer, application service layer, and presentation layer—supports interoperability, data consistency, and platform scalability. Data models, such as DFD and ERD, ensure the integration of information across accreditation modules and quality monitoring of learning. The resulting interface design provides intuitive and efficient access for users from various institutional roles. Expert validation indicates that the PRIMA PPMPP design model meets the needs of the quality assurance process and is feasible for implementation. This research contributes conceptually to the development of a data-based quality assurance system in vocational education and can serve as a reference for other institutions building integrated quality data centers.