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Journal : International Journal of Visual and Performing Arts

Method design of interactive digital devices to support the workspace comfort Athifa Sri Ismiranti; Akhmadi Akhmadi; Arini Arumsari; Mahendra Nur Hadiansyah; Alfito Aji Denandra; Sarah Nurul Azizah
International Journal of Visual and Performing Arts Vol 5, No 2 (2023)
Publisher : ASSOCIATION FOR SCIENTIFIC COMPUTING ELECTRICAL AND ENGINEERING (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/viperarts.v5i2.1083

Abstract

There are many alterations and adaptations of the workspaces after the Covid-19 pandemic. Nowadays, workspaces are required to have flexibility in facilitating physical and virtual activities, work-from-home (WFH), and work-from-office (WFO) activities. Besides, workspaces must provide comfort based on user preferences and demand to support workers’ health and productivity. In order to answer these problems, the design of interactive digital devices that can be adjusted according to physical needs, activities, and preferences is needed to support the ideal workspace comfort. The research method used in this research is a literature review related to ideal workspace comfort standards and an assessment of the Arduino as an interactive digital device to produce an interactive digital device method design that can detect ideal comfort and be applied to workspaces. The result shows that as an interactive digital device, Arduino can be implemented in a workspace to detect and produce ideal workspace comfort regarding lighting, noise, temperature, and humidity. Arduino also supports flexibility and varied demand in a workspace because of its adjustable artificial intelligence feature. The ideal standard of workspace differs based on the activities and geographical conditions of the country and is related to the varied preferences of its users. Based on its complexity, for further research to be carried out, it is recommended to conduct a case study of ideal workspace interior design with an Arduino device in a specific place to generate more accurate data and suitable workspace design.
Experimentation of BIM and AI software to support Adaptive Learning System in interior design course Ismiranti, Athifa Sri; Sudarisman, Irwan; Rusyda, Hana Faza Surya; Akhmadi, Akhmadi
International Journal of Visual and Performing Arts Vol 6, No 2 (2024)
Publisher : ASSOCIATION FOR SCIENTIFIC COMPUTING ELECTRICAL AND ENGINEERING (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/viperarts.v6i2.1538

Abstract

Current undergraduate students, particularly Generation Z, are digital natives who have grown up with digital technology and exhibit unique learning characteristics that necessitate new approaches in higher education. An Adaptive Learning System in education involves leveraging technology to accommodate individual students' unique needs and preferences. This research aims to enhance learning effectiveness and design processes in interior design courses, with the case study Interior Design II course at Telkom University, Indonesia. The course currently offers limited software options for interior layout design, which may hinder students' abilities and preferences. This study compares three software tools—Autodesk AutoCAD, Building Information Modeling (BIM) software Autodesk Revit, and Artificial Intelligence (AI)-based plugin PlanFinder—to determine which is most effective in improving students' understanding and simplifying the design process. The research methodology employs a mixed-method approach, integrating qualitative methods such as literature reviews and Focus Group Discussions (FGDs) with quantitative methods like experimentation workshops and pre-test and post-test questionnaires analyzed using SPSS software. The results demonstrate that Autodesk Revit, a BIM software, notably enhances the design process's effectiveness, particularly within the Interior Design II course context. Consequently, the study recommends the implementation of Adaptive Learning Systems that allow students to select software based on their capabilities and preferences. The three software tools/plugins examined in this study can be considered for integration into interior design courses. Furthermore, future research should seek to broaden the sample size and evaluate additional AI tools in interior design courses for comparative analysis