Implementasi Augmented Reality Sebagai Media Visualisasi Arsitektur Gedung Fakultas Ilmu Komputer Universitas Jember Berbasis Mobile

Abstract

This study aims to design and implement a mobile-based Augmented Reality (AR) application as an architectural visualization media for the Faculty of Computer Science building at the University of Jember using the ADDIE development model. The method employed is Research and Development (R&D) with a descriptive quantitative approach, following the five ADDIE phases from needs analysis to product evaluation. The application was developed using Unity 3D, AR Foundation, and C# programming language with a marker-based AR approach, then tested through Black-Box Testing and performance testing on ten Android devices. The results showed that all functional requirements were fulfilled with a 100% success rate in Black-Box Testing, along with an average frame rate of 52–60 FPS, exceeding the minimum standard of 30 FPS recommended by Google ARCore. Field implementation also confirmed system stability with a 100% marker detection success rate and an average detection time of 3 seconds. The novelty of this research lies in the adaptation of the ADDIE model which has been predominantly used in instructional development into the software engineering domain for AR applications, producing structured design documentation (UML, System Request, indexed specifications) that ensures traceability and reproducibility. This research differs from previous studies that focused more on final product demonstrations without systematic software engineering documentation, thereby contributing to the advancement of knowledge in Software Engineering, particularly Software Design, as a case study of structured development model implementation in mobile-based AR applications. This study concludes that the ADDIE model was successfully adapted systematically and the resulting application has met all specifications and is feasible for use on mid range to high-end Android devices. However, this conclusion is limited to the context of marker-based AR without quantitative measurement of the effectiveness in improving users' spatial abilities. Recommendations for future research include developing the application with a markerless tracking approach based on plane detection or SLAM, adding text-based room search features, and integrating real-time lecture schedule information.