Journal of Artificial Intelligence in Architecture <p><a href="">Journal of Artificial Intelligence in Architecture (JARINA)</a> is currently accepting manuscripts from professionals, teachers, researchers, and students in various backgrounds, including the following disciplines:</p> <ul> <li>Architecture</li> <li>Urban Design</li> <li>Building Sciences</li> <li>Informatics Engineering in Architecture</li> <li>Neuro - Psychology in Architecture</li> </ul> <p><a href="">Topics of interest</a> may include but not limited to: digital art, informatics, neuroscience, and technology in architecture.</p> <p> </p> <p>The first volume will be <strong><span style="text-decoration: underline;">free of article processing charge.</span></strong></p> <p><strong><span style="text-decoration: underline;"> </span></strong></p> <p>JARINA publishes twice a year in <strong>February and August</strong></p> Universitas Atma Jaya Yogyakarta en-US Journal of Artificial Intelligence in Architecture 2962-5629 <p>Authors who publish with this journal agree to the following terms:</p> <p>1.Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="" target="_blank" rel="noopener">Creative Commons</a> that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.</p> <p>2.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.</p> <p>3.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).</p> Introduction and Demo of Virtual Reality Technology to Initiate Active Learning in Architectural Design <p>Architectural education is adapting to the demands of efficient, technology-driven practices, with virtual reality (VR) emerging as a critical tool in bridging communication gaps between architects and clients. This study, conducted by lecturers at Institut Teknologi Indonesia, focuses on their experience implementing VR technology in the High-rise Building Technology class. The initiative spans four sequential stages, with the introduction and demo executed hybridly (online and offline). The authors emphasize the importance of knowledge induction and firsthand demonstrations to familiarize students with VR. Notably, external instructors proficient in VR technology participate in the program. Student engagement and enthusiasm are evident, with offline demo attendance surpassing the online VR introduction seminar. The COVID-19 pandemic has affected students' motivation to learn, and the hands-on VR experience is a revitalizing approach. The two-way interaction between instructors and students enhances interest in in-person attendance. The authors advocate for the continued development of this experience in architectural education, promoting an active learning system using VR across various courses. The paper underscores the potential of VR technology to invigorate architectural education and enhance student engagement in the post-pandemic learning landscape.</p> Intan Findanavy Ridzqo Aliviana Demami Copyright (c) 2023 Aliviana Demami, Intan Findanavy Ridzqo 2024-02-09 2024-02-09 3 1 1 10 10.24002/jarina.v3i1.6988 The Organic Challenge: The Organic Challenge: Cultivating Conscious Design for Biodigital Tectonics within AI’s Prompt-to-Pixel Process <p>The fusion of digital advancements and biological systems is transforming modern-day architecture, and this bio-digital approach, when paired with AI image generation models, promises novel design possibilities. The major drawback of this merger is the dismal performance of AI text-to-image models in translating organic tectonic details into architecture. This study examines the complexity of processes, materials, and techniques necessary in a bio-digital architectural approach. Through a series of digital trials, it identifies the need for sophisticated computational models that can capture the complex intricacies and subtle nuances present in living organisms. Before the testing, a set of parameters considered the limitation of how much tectonic information an image could portray. The Nautilus Shell, ferns, mushrooms, seahorses, and grasshoppers were taken as inspiration models because of varying biological configurations. Next, two AI image-generating tools, Midjourney and Stable Diffusion, were used with three different prompt types, each with varying degrees of complexity drawn from five organic systems. A critical analysis of AI-generated images led to the conclusion that, despite AI's exceptional abilities in creating visual content, the complex comprehension of biological systems and their conversion into architectural designs faced significant challenges.</p> Farina Shahid Copyright (c) 2024 Farina Shahid 2024-02-09 2024-02-09 3 1 11 23 10.24002/jarina.v3i1.8157 Generative Artificial Intelligence to Enhance Architecture Education to Develop Digital Literacy and Holistic Competency <p class="p1">This research investigates the impact of Generative Artificial Intelligence (GenAI) on digital literacy development and holistic competencies in Architecture education. The research design focuses on applying GenAI tools such as ChatGPT, Midjourney, BricsCAD BIM, and VR/AR software and their influence on architectural students' overall competencies. This paper uses a mixed research approach combining a case study of Architecture students' progress in a residential revisitation project, using Midjourney, BricsCAD BIM, and VR/AR software, with an online questionnaire survey administered to 350 undergraduate students at two leading universities in Mainland China and Hong Kong in the 2023-2024 school year. This approach aims to deepen understanding of GenAI's influence on conceptual creativity, initiative, self-management, and stress tolerance within a holistic competency framework. The research results indicate that architecture students frequently use GenAI tools during the design concept stage, suggesting their relevance to specific pedagogy in-studio learning and conceptual creativity. Additionally, the findings reveal a potential correlation between frequent GenAI tool usage, improved time management, and reduced anxiety among Architecture students. The results enhance understanding of digital technology in Architecture education while providing valuable insights for future GenAI implementations. The study highlights the potential benefits of incorporating GenAI, emphasizing their role in fostering creativity, effective time management, and stress tolerance among Architecture students.</p> Tris Kee Blair Kuys Ronnel King Copyright (c) 2024 Dr. Tris Kee , Professor Blair Kuys, Dr. Ronnel King 2024-02-09 2024-02-09 3 1 24 41 10.24002/jarina.v3i1.8347 Comparative Perspectives: Exploring Workflow Efficiencies of BIM and CAD in 3D Modelling <p><em>Building Information Modelling </em>(BIM) is a new technology to make genuine project contributions, especially in the industry, architecture, and construction sectors. However, in practice, many professional workforces choose <em>computer-aided design </em>(CAD) as the primary technology<em>, which </em>has formerly appeared and is further comprehensible. <em>Building Information Modelling </em>offered different perspectives on purpose to facilitate designers or architects to expertise in various fields<em>. Building Information Modelling </em>(BIM) contains informative data that can use some expertise as a solution to make the occupation more coherent. This research aims to comprehend the workflow differences between <em>Computer Aided Design </em>(CAD) and <em>Building Information Modelling </em>(BIM) system technology. We collated methods by reviewing some literature and reviewing case studies. Then, we compare the workflow and conclude which is more effective for architectural design. In this research, we explore the difference between BIM's workflow and Cad's workflow to know which is more effective. So, we conclude and can apply the technology appropriately in the workflow needed so that it can simplify the workflow.</p> Henricus Arya Wisnu Wardana Audrey Maura Meliana Putri Suman Steffania Jacinda Copyright (c) 2024 Henricus Arya Wisnu Wardana, Audrey Maura, Meliana Putri Suman, Steffania Jacinda 2024-02-09 2024-02-09 3 1 42 52 10.24002/jarina.v3i1.8321 Computational Methods and Artificial Intelligence in The Architectural Pre-Design Process (Case Study: House Design) <p style="font-weight: 400;">The current development of information technology infrastructure has positively impacted the ease with which people can carry out work activities physically and creatively. Artificial intelligence, which is currently starting to penetrate the world of visual design and architecture, is starting to develop from integrating design methods to methods of presenting or communicating architecture. In this study, aspects of artificial intelligence are used as a pre-design method, which is considered to help speed up decisions in design communication. The problem raised in this study is how optimal the involvement of computing and artificial intelligence is in providing pre-design considerations in the case of simple residential houses, especially in the analysis, space, and visual aspects. This study aims to obtain the methods and influence of computing and artificial intelligence in formulating pre-designs and generating understanding regarding the methods of their use. Several analysis tools are used for the spatial approach: the space syntax using DepthmapX software, solar analysis using the Shadedat plugin, and the visual shape of the building using Stable Diffusion. This research uses an experimental approach to obtain the desired design results. This study's findings explain that applying appropriate computational and artificial intelligence methods will produce an effective and efficient design process. With the correct sequence, it will have a measurable design process that can be assessed well.</p> Widi Cahya Yudhanta Irwan Yudha Hadinata Copyright (c) 2024 Widi cahya Yudhanta, Irwan Yudha Hadinata 2024-02-09 2024-02-09 3 1 53 60 10.24002/jarina.v3i1.8431 Front Matter of JARINA Vol.3 No.1, 2024 Prasasto Satwiko Copyright (c) 2024 Prasasto Satwiko 2024-02-09 2024-02-09 3 1 Back Matter of Jarina Vol. 3 No1 ,2024 Prasasto Satwiko Copyright (c) 2024 Prasasto Satwiko 2024-02-09 2024-02-09 3 1