Penerapan Generative AI dan Building Information Modeling (BIM) dalam Efisiensi Alur Kerja Desain Arsitektur Tropis
DOI:
https://doi.org/10.51903/nva5xr07Keywords:
Generative AI, BIM, Tropical Architecture, Parametric Design, InteroperabilityAbstract
The increasing demand for efficient and climate-responsive building design has encouraged the adoption of digital technologies in architectural practice. However, conventional design workflows often require lengthy iterations due to the separation of creative exploration and technical validation. This study aims to evaluate the effectiveness of integrating Generative Artificial Intelligence (Generative AI) and Building Information Modeling (BIM) in improving the efficiency of tropical architectural design while maintaining geometric accuracy and thermal performance. An experimental comparative approach was applied to a five-story office building in Jakarta, Indonesia. The workflow integrated AI-based design generation, BIM-based parametric modeling, interoperability assessment, clash detection, and thermal performance evaluation using the Overall Thermal Transfer Value (OTTV) method. The results show that the proposed AI-BIM workflow reduced design duration from 90.0 to 17.0 hours, achieving an efficiency rate of 81.11%. The average geometry interoperability error was 3.28%, while the selected kinetic façade achieved an OTTV value of 31.22 W/m², satisfying SNI 6389:2020 requirements. Expert validation also indicated high feasibility, with average scores above 4.00 on a five-point Likert scale. The novelty of this study lies in the development of a standardized workflow that transforms AI-generated visual assets into engineering-valid BIM parametric objects for tropical architecture. The findings demonstrate that AI-BIM integration can significantly enhance design productivity, thermal performance, and practical implementation in the construction industry.
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Copyright (c) 2026 Naren Wicaksana, Celine Mahastuti (Author)
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