An Ontology-Driven Adaptive User Interface Framework for Indonesian Student Wellbeing - Bhanu Sri Nugraha; Muhammad Suyanto; Kusrini Kusrini; Ema Utami (INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi, 2026)
Background: The personalization of digital learning environments to support student wellbeing presents a significant challenge due to the need for integrating multi-dimensional contextual factors. Existing adaptive user interface (AUI) approaches often rely on ad-hoc rule-based systems or simpler adaptive mechanisms, lacking the formal semantic grounding required to handle the intricate interdependencies between diverse wellbeing dimensions and corresponding UI adaptations. Objective: This research aimed to design, develop, and formally validate a novel semantic framework for a context-aware AUI specifically tailored to provide a formal foundation for supporting multidimensional student wellbeing factors. Methods: The methodology involved creating a detailed "Context Mapping" table to establish relational scenarios between student contexts, wellbeing factors, and UI adaptations. Subsequently, a Semantic Taxonomy was engineered and implemented as a Web Ontology Language (OWL) model in Protégé. Its relational data retrieval capabilities were demonstrated via the SPARQL Protocol. The principal outcome of this investigation is the formal validation of the ontology using the HermiT reasoner. This study utilized a comprehensive literature review to formulate its context mapping, followed by a formal modeling and validation methodology. Results: Using the HermiT reasoner conclusively determined that the model is both coherent and consistent. The research successfully translated qualitative Indonesian student wellbeing requirements into a formal, computationally tractable semantic framework. Conclusion: The developed semantic framework provides a validated foundation for the deployment of intelligent, context-aware applications designed to enhance Indonesian student wellness in higher education. This research successfully multi-dimensional requirements for a context-aware student wellbeing application into a robust, and scalable framework.