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Penerapan Perangkat Lunak RStudio untuk Penaksiran Parameter Model Spatial Autoregressive

KUBIK: Jurnal Publikasi Ilmiah Matematika · Vol. 8 No. 1 (2023) · pp. 50–64

DOI
10.15575/kubik.v8i1.30037
ISSN
2686-0341, 2338-0896
Published
2023-05-19
Publisher
Department of Mathematics, Faculty of Science and Technology, UIN Sunan Gunung Djati Bandung
Language
ind

Abstract

Research and analysis that are not only based on time (temporal) but also on space (spatial) require tools in the form of software to ensure that the data analysis and processing yield good, fast, and accurate results. One of the software tools that can be used for this purpose is RStudio software. The advantages of RStudio include being open-source software (OSS), which can be used freely without cost, and it has many packages and functions that can facilitate data processing. One of the spatial-based analyses is spatial data analysis. The structure within RStudio allows users to call functions related to spatial data analysis, perform computations with sparse matrices (matrices with many zero values), such as spatial weight matrices, estimation of spatial model parameters, and so on. This research examines the application of RStudio software in estimating the parameters of a first-order Spatial Autoregressive (SAR) model using the Maximum Likelihood Estimation (MLE) method on the data of the designation of Intangible Cultural Heritage (ICH) in Indonesia. Based on the results of applying RStudio software, a first-order SAR model with a Queen contiguity weight matrix for the categories of Traditional Customs, Rituals, and Celebrations (TCRC) and Performing Arts (PA) with the minimum Akaike Information Criterion (AIC) value and maximum pseudo-Â value was obtained for predicting the designation data of ICH in Indonesia. The application of RStudio software to the first-order SAR model for the designation data of ICH in Indonesia speeds up and simplifies calculations, making it suitable as a recommendation for relevant agencies such as the Department of Culture, Tourism, Youth, and Sports (Disbudparpora).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
Firdaus Ryan PratomoAffiliation 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) 
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	<dc:title xml:lang="en-US">Penerapan Perangkat Lunak RStudio untuk Penaksiran Parameter Model Spatial Autoregressive</dc:title>
	<dc:creator>Salsabil, Tsuroyya</dc:creator>
	<dc:creator>Kusuma, Dianne Amor</dc:creator>
	<dc:creator>Ruchjana, Budi Nurani</dc:creator>
	<dc:subject xml:lang="en-US">RStudio</dc:subject>
	<dc:subject xml:lang="en-US">Spatial Autoregressive (SAR)</dc:subject>
	<dc:subject xml:lang="en-US">Spatial Weight Matrix</dc:subject>
	<dc:description xml:lang="en-US">Research and analysis that are not only based on time (temporal) but also on space (spatial) require tools in the form of software to ensure that the data analysis and processing yield good, fast, and accurate results. One of the software tools that can be used for this purpose is RStudio software. The advantages of RStudio include being open-source software (OSS), which can be used freely without cost, and it has many packages and functions that can facilitate data processing. One of the spatial-based analyses is spatial data analysis. The structure within RStudio allows users to call functions related to spatial data analysis, perform computations with sparse matrices (matrices with many zero values), such as spatial weight matrices, estimation of spatial model parameters, and so on. This research examines the application of RStudio software in estimating the parameters of a first-order Spatial Autoregressive (SAR) model using the Maximum Likelihood Estimation (MLE) method on the data of the designation of Intangible Cultural Heritage (ICH) in Indonesia. Based on the results of applying RStudio software, a first-order SAR model with a Queen contiguity weight matrix for the categories of Traditional Customs, Rituals, and Celebrations (TCRC) and Performing Arts (PA) with the minimum Akaike Information Criterion (AIC) value and maximum pseudo- value was obtained for predicting the designation data of ICH in Indonesia. The application of RStudio software to the first-order SAR model for the designation data of ICH in Indonesia speeds up and simplifies calculations, making it suitable as a recommendation for relevant agencies such as the Department of Culture, Tourism, Youth, and Sports (Disbudparpora). </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>2023-05-19</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/30037</dc:identifier>
	<dc:identifier>10.15575/kubik.v8i1.30037</dc:identifier>
	<dc:source xml:lang="en-US">KUBIK: Jurnal Publikasi Ilmiah Matematika; Vol. 8 No. 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika; 50-64</dc:source>
	<dc:source xml:lang="id-ID">KUBIK; Vol 8 No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika; 50-64</dc:source>
	<dc:source>2686-0341</dc:source>
	<dc:source>2338-0896</dc:source>
	<dc:source>10.15575/kubik.v8i1</dc:source>
	<dc:language>ind</dc:language>
	<dc:relation>https://journal.uinsgd.ac.id/index.php/kubik/article/view/30037/9869</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2023 Tsuroyya Salsabil, Dianne Amor Kusuma, Budi Nurani Ruchjana</dc:rights>
</oai_dc:dc>