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Nimas Sekarlangit
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jarinauajy@gmail.com
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Gedung Thomas Aquinas Jl. Babarsari No.44, Caturtunggal, Kec. Depok, Sleman, Yogyakarta 55281
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INDONESIA
Journal of Artificial Intelligence in Architecture
Published by Universitas Atma Jaya Yogyakarta
ISSN : 29625629     EISSN : 28296257     DOI : https://doi.org/10.24002/jarina
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT
Journal of Artificial Intelligence in Architecture (JARINA) is currently accepting manuscripts from professionals, teachers, researchers, and students in various backgrounds, including the following disciplines: Architecture Urban Design Building Sciences Informatics Engineering in Architecture Neuro - Psychology in Architecture Topics of interest may include but not limited to: digital art, informatics, neuroscience, and technology in architecture.
Arjuna Subject : Teknik (semua kategori) - Arsitektur
Articles 89 Documents
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Front Matter of JARINA Vol.5 No.1, 2026 Prasasto Satwiko
Journal of Artificial Intelligence in Architecture Vol. 5 No. 1 (2026): Artificial Intelligence for Human-Centric Performance: Integrating Neuroarchite
Publisher : Universitas Atma Jaya Yogyakarta

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Back Matter of JARINA Vol.5 No.1, 2026 Prasasto Satwiko
Journal of Artificial Intelligence in Architecture Vol. 5 No. 1 (2026): Artificial Intelligence for Human-Centric Performance: Integrating Neuroarchite
Publisher : Universitas Atma Jaya Yogyakarta

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Digital Technology as an Enabler for Sustainable Natural Resource Management Policies in Indonesia Elisabeth Budianto; Christina Esti Wardani
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jarina.v5i2.11234

Abstract

This study investigates the role of digital technologies in supporting sustainable natural resource management in Indonesia. The research aims to identify dominant technologies and clarify their contributions to policy-oriented sustainability frameworks. A mixed-methods approach was applied, combining a systematic review of Scopus-indexed journals, thematic coding of sustainability elements, AI-assisted clustering of architectural technology usage, and quantitative frequency mapping. The results highlight the prominence of the Internet of Things (IoT, 45.88%) and Building Information Modelling (BIM, 30.63%) in enabling real-time monitoring and integrated infrastructure planning. Complementary tools such as ArcGIS, Google Earth Engine, Blockchain, and VR/AR further support transparency, spatial analysis, and eco-friendly design. By synthesising these contributions, the study demonstrates how digital technologies enable sustainable resource management strategies in Indonesia and provides a foundation for future research and implementation
YOLO-Based Identification and AI Generative Design of Nusantara Architectural Element through Kisho Kurokawa’s Symbiosis Concept David Ricardo; Guruh Kristiadi Kurniawan; Antusias Nuzukhrufa; Fasha Nurliansyah Mahendra
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jarina.v5i2.13626

Abstract

This research is rooted in the fundamental practice of combining two forms, long pursued by the Japanese architect Kisho Kurokawa, who gave rise to the concept of Symbiosis (Combining two different elements). The purpose of this research is to utilise artificial intelligence, such as YOLO v8, for identification and diffusion models to produce new building images with the Nusantara and Kisho Kurokawa concepts. The problem of this research is how Kisho Kurokawa's concept can be integrated into Nusantara architecture by re-identifying its elements and transforming them. The purpose of this research is to identify and transform the facade with the Nusantara and Symbiosis concepts. The method used is experimental, involving the collection of Lampung building datasets from the Nusantara era, followed by initial identification using YOLO v8 and classification of character similarities based on the symbiosis concept. The final step is to transform the Nusantara form (stable diffusion) for re-identification with YOLO v8 against the Nusantara facade elements. The results show that YOLO v8 can still identify various models of Nusantara architectural elements, even when they have changed shape, based on the contextual similarity to Kisho Kurokawa's Symbiosis concept.
Between Intuition and Instruction: Comparison of Generative Models in Symbolic Design Ideation Case Study of IKN Garuda Palace Bramasta Putra Redyantanu
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jarina.v5i2.13749

Abstract

This study aims to map the comparison of various artificial intelligence (AI)-based generative models, particularly the shift from design intuition to text-based command instructions, as a potential source of ideas in symbolic architecture design. While generative AI is increasingly adopted in creative fields, there remains a critical research gap in the systematic evaluation of how different conversational platforms respond to abstract, symbol-based architectural narratives during early-stage ideation. To address it, this study employs a qualitative-comparative case study approach to evaluate three popular text-to-image generative models: Copilot, ChatGPT, and Gemini. The study was conducted by deploying identical command prompts based on the symbolic narrative of the Garuda National Capital (IKN) Palace and comparing the outputs across dimensions such as visual quality, contextual accuracy, diversity of ideas, generation speed, and adaptability to change. The concrete findings reveal distinct computational behaviours: Copilot excels at architectural integration through monumental abstraction, ChatGPT prioritises literal and explicit symbolic replication, and Gemini offers highly fluid, narrative-driven conceptual sketches. Based on these results, the concept of AI's potential is proposed through three main discussion frameworks: variation exploration, productivity efficiency, and communication visualisation. This study contributes a new evaluative framework for human-machine interaction in architectural pedagogy and practice, demonstrating how tailored prompt descriptions can transform AI from a passive visualisation tool into an active, reflective conceptual partner.
Vision Transformer-Based Recognition of Riau Malay Architectural Features with Cross-Regional Comparison for Digital Heritage Documentation Heri Pramono; Sri Winiarti; Abdul Fadlil; Sunardi
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jarina.v5i2.14591

Abstract

Traditional Riau Malay architecture requires systematic digital documentation for heritage preservation. This study evaluates a Vision Transformer (ViT-B/16) model initialised with ImageNet-1K pretrained weights for recognising Riau Malay architectural features, using Pontianak Malay architecture for cross-regional comparison. The dataset was constructed from 24 architectural videos covering roof shapes, building structures, ornaments, windows, staircases, and full-building views. Using automated spatiotemporal segmentation at five frames per second, 13,230 frames were extracted, resized to 224×224 pixels, normalised, augmented, and divided into 16×16-pixel patches. Evaluation on a balanced, held-out test set of 32 clips yielded an overall accuracy of 84.38%, macro precision of 84.51%, macro recall of 84.38%, and macro F1-score of 84.36%. Distinctive elements, such as roofs, windows, staircases, and full buildings, achieved higher recognition performance when clearly visible. Conversely, partially visible structures and detailed ornaments exhibited variable performance due to lighting, viewpoint, and visual complexity. Given the single hold-out split and the limited number of source videos, these findings are preliminary; high feature-specific accuracies should not imply perfect recognition or generalizability. Nonetheless, the results demonstrate ViT-B/16’s strong potential to support the digital recognition of Malay architectural heritage. Future work should incorporate grouped five-fold cross-validation, independent building-level testing, CNN baseline comparisons, ROC–AUC analysis, and attention map visualisations.
Microclimate-Based Assessment of Outdoor Thermal Comfort in The Provincial Police Headquarters Park Using Andrew Marsh’s Sun Path Tool Karin Ginting; Dimitri Indah Puspita Sari; Dhita Wahyu Anggraeni
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jarina.v5i2.15101

Abstract

Urban parks play an important role in enhancing environmental quality and supporting public activities. Yet, studies integrating field-based microclimate measurements with solar path simulation to evaluate outdoor thermal comfort in tropical urban parks remain limited. This study analyses the microclimatic characteristics of Polda Park and their implications for outdoor thermal comfort. The novelty of this study lies in integrating field-based measurements with Andrew Marsh’s Sun Path Tool to assess solar exposure and shading patterns for climate-responsive landscape design. Andrew Marsh’s Sun Path Tool was selected to simulate solar paths and shading patterns for climate-responsive landscape assessment. A descriptive quantitative approach was employed using field measurements of air temperature and relative humidity across three observation zones: the jogging track, retention pond, and playground. Outdoor thermal comfort was evaluated using the Temperature Humidity Index (THI), while the Sun Path Tool was used to simulate solar exposure and shading patterns. The results showed that most areas were classified as partially uncomfortable during the morning and afternoon (THI = 25.5-28.9), whereas all observation zones were uncomfortable at midday (THI =29.00-30.3) due to intense solar radiation and limited shading. The integration of field measurements with solar path simulation provides a reliable basis for climate-responsive landscape design. It supports evidence-based planning to improve outdoor thermal comfort in tropical urban parks. The proposed approach demonstrates how computational environmental simulation can support data-informed landscape decision-making within the context of Artificial Intelligence in Architecture.
Front Matter Vol. 5 No. 2 August 2026 Prasasto Satwiko
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Back Matter Vol. 5 No. 2 August 2026 Prasasto Satwiko
Journal of Artificial Intelligence in Architecture Vol. 5 No. 2 (2026): Artificial Intelligence for Architecture: From Sustainable Management to Digita
Publisher : Universitas Atma Jaya Yogyakarta

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