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Penerapan Model Geographically Weighted Regression pada Data Penetapan Warisan Budaya Takbenda di Indonesia

KUBIK: Jurnal Publikasi Ilmiah Matematika · Vol. 9 No. 1 (2024) · pp. 60–70

DOI
10.15575/kubik.v9i1.33492
ISSN
2686-0341, 2338-0896
Published
2024-05-25
Publisher
Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung
Language
ind

Abstract

Intangible Cultural Heritage (WBTb) determination data in Indonesia is a cultural investment that needs to be preserved. One of the efforts to preserve WBTb is to determine the cultural preservation factors that influence the WBTb determination data in Indonesia. These factors include Percentage of Population Watching Performances/Art Exhibitions (PPWP), Percentage of Population Using Regional Languages (PPURL), and Percentage of Households Using Traditional Products (PHUTP). However, the different cultural wealth in each province results in spatial heterogeneity, resulting in differences in the determination of cultural preservation factors in each province. This determination can be done with the Geographically Weighted Regression (GWR) model. This study aims to apply the GWR model with Fix Gaussian Kernel, Fix Bisquare Kernel, and Fix Tricube Kernel weighting to determine cultural preservation factors in WBTb determination data in Indonesia so that it can be known what cultural preservation factors are most influential in each region. The research findings show the existence of spatial heterogeneity only in the category of WBTb designation data for Performing Arts (PA) and Oral Expression Tradition (OET), as well as different GWR models in each province that reflect differences in cultural preservation factors. Evaluation with the coefficient of determination shows that the GWR model with the Fix Gaussian Kernel weighting function is the best model for the PA category.Â

Keywords

Collaboration network of the authors

29 authors · 78 co-authorship links

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  • Padjadjaran University
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Bambang SuhandiAffiliation unknown2
Kankan ParmikantiAffiliation unknown2
Tsuroyya SalsabilAffiliation unknown2
Aay SusilawatiAffiliation unknown1
Lilis MarinaAffiliation unknown1
A ArcatAffiliation unknown1
S SohibunAffiliation unknown1
Muchamad Subali NotoAffiliation unknown1
Astri WahyuniAffiliation unknown1
Ika WulandariAffiliation unknown1
Sri Adi WidodoAffiliation unknown1
Estiyan DwipriyokoAffiliation unknown1
Annis Deshinta AyuningtyasAffiliation unknown1
Widowati PusporiniAffiliation unknown1
Hera KhoirunnisaAffiliation unknown1
iin IrianingsihAffiliation unknown1
Endang Soeryana HasbullahAffiliation unknown1
Novi - SaputriAffiliation unknown1
Atika Tresna AriantoAffiliation unknown1
valda azka nadhiraAffiliation unknown1
Atje Setiawan AbdullahPadjadjaran University1
Anggraeni AAffiliation unknown1
Nurdeni NurdeniAffiliation unknown1
Hardianto AAffiliation unknown1
Muthalib AAffiliation unknown1
Husein H BahtiAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.uinsgd.ac.id/index.php/kubik/oai, first harvested 7 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="id-ID">Penerapan Model Geographically Weighted Regression  pada Data Penetapan Warisan Budaya Takbenda di Indonesia</dc:title>
	<dc:creator>Pratomo, Firdaus Ryan</dc:creator>
	<dc:creator>Kusuma, Dianne Amor</dc:creator>
	<dc:creator>Ruchjana, Budi Nurani</dc:creator>
	<dc:subject xml:lang="id-ID">Keywords</dc:subject>
	<dc:subject xml:lang="id-ID">Geographically Weighted Regression</dc:subject>
	<dc:subject xml:lang="id-ID">Intangible Cultural Heritage</dc:subject>
	<dc:subject xml:lang="id-ID">Spatial Heterogeneity</dc:subject>
	<dc:description xml:lang="id-ID">Intangible Cultural Heritage (WBTb) determination data in Indonesia is a cultural investment that needs to be preserved. One of the efforts to preserve WBTb is to determine the cultural preservation factors that influence the WBTb determination data in Indonesia. These factors include Percentage of Population Watching Performances/Art Exhibitions (PPWP), Percentage of Population Using Regional Languages (PPURL), and Percentage of Households Using Traditional Products (PHUTP). However, the different cultural wealth in each province results in spatial heterogeneity, resulting in differences in the determination of cultural preservation factors in each province. This determination can be done with the Geographically Weighted Regression (GWR) model. This study aims to apply the GWR model with Fix Gaussian Kernel, Fix Bisquare Kernel, and Fix Tricube Kernel weighting to determine cultural preservation factors in WBTb determination data in Indonesia so that it can be known what cultural preservation factors are most influential in each region. The research findings show the existence of spatial heterogeneity only in the category of WBTb designation data for Performing Arts (PA) and Oral Expression Tradition (OET), as well as different GWR models in each province that reflect differences in cultural preservation factors. Evaluation with the coefficient of determination shows that the GWR model with the Fix Gaussian Kernel weighting function is the best model for the PA category. </dc:description>
	<dc:publisher xml:lang="en-US">Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung</dc:publisher>
	<dc:date>2024-05-25</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.uinsgd.ac.id/index.php/kubik/article/view/33492</dc:identifier>
	<dc:identifier>10.15575/kubik.v9i1.33492</dc:identifier>
	<dc:source xml:lang="en-US">KUBIK: Jurnal Publikasi Ilmiah Matematika; Vol. 9 No. 1 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika; 60-70</dc:source>
	<dc:source xml:lang="id-ID">KUBIK; Vol 9 No 1 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika; 60-70</dc:source>
	<dc:source>2686-0341</dc:source>
	<dc:source>2338-0896</dc:source>
	<dc:source>10.15575/kubik.v9i1</dc:source>
	<dc:language>ind</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/kubik/article/view/33492/10945</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2024 Firdaus Ryan Pratomo</dc:rights>
</oai_dc:dc>