Decoding spatial layout patterns of traditional houses in urban kampung settlements

Understanding and identifying the spatial layout patterns of traditional houses is a pivotal feature for preserving and enhancing the cultural heritage of twelve houses which have been an object to be studied. This research investigates a comprehensive study to understand a particular architectur...

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Bibliographic Details
Main Authors: Nova Asriana, Rendy Perdana Khidmat
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2024-12-01
Series:Journal of Architecture and Urbanism
Subjects:
Online Access:https://journals.vilniustech.lt/index.php/JAU/article/view/20832
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Summary:Understanding and identifying the spatial layout patterns of traditional houses is a pivotal feature for preserving and enhancing the cultural heritage of twelve houses which have been an object to be studied. This research investigates a comprehensive study to understand a particular architectural plan in a participa- tive community of design processing on decoding spatial layout patterns through a generative Justified Plan Graph (g-JPG) as a grammatical spatial approach. This research examines the grammar using the rule-based spatial structure of traditional housing in three urban kampung in Indonesia. This method applies three pro- cedures, such as collecting data, extracting jpg grammar, and formulating jpg grammar. Regarding the in- vestigated result, indigenous and non-indigenous dwellers have mostly constructed the spatial configuration axially and created a spatial penetration or intersectional space on movement by generating and distancing social concept long models in their traditional houses. Another finding is that the houses’ spatial layouts are integrated as spacious hall-centred, representing a rule-structure and form-based. It is found that this study can serve as a valuable resource for architects and researchers who are interested in preserving and revital- izing the architectural identity of traditional housing.
ISSN:2029-7955
2029-7947