Melola Discovery

← Melola Discovery

Journal

Spatial Autocorrelation of East Java's Economic Growth Using Cluster-Based Weights

Economics Development Analysis Journal · Vol. 13 No. 4 (2025)

DOI
10.15294/edaj.v13i4.19161
ISSN
2502-2725, 2252-6560
Published
2025-03-09
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

This study incorporates a spatial clustering technique into the formation of a spatial weight matrix as an alternative to the traditional exogenous matrix, aiming to better capture spatial dependencies. The approach is applied to analyze the spatial autocorrelation of economic growth in East Java’s regencies and municipalities using 2019–2021 data. Spatial clusters are identified based on GDP growth (GGDP), Human Development Index (HDI), population density (Dens), and geographical coordinates. These clusters are used to define a customized spatial weight matrix, where regions within the same cluster are designated as neighbors. Moran’s I, calculated using the customized spatial weight matrix, detects significant spatial autocorrelation in GDP growth for all three years, with consistently lower p-values compared to the traditional contiguity-based matrix. For example, in 2020, Moran’s I using the customized matrix yielded a p-value of 0.099 (significant at the 10% level), while the traditional matrix produced a non-significant p-value of 0.7965. These results demonstrate that spatial clustering extends the scope of spatial interaction beyond adjacent regions to include those with similar characteristics. The findings highlight the effectiveness of this method in providing a more nuanced and robust framework for analyzing spatial dependencies in economic growth.

Keywords

Collaboration network of the authors

24 authors · 68 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University of Brawijaya
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Solimun SolimunUniversity of Brawijaya2
Atiek IrianyUniversity of Brawijaya2
Loekito Adi SoehonoAffiliation unknown2
Agus Fachrur RozyUniversity of Brawijaya1
Eni SumarminingsihUniversity of Brawijaya1
Nabila Ayunda SoviaAffiliation unknown1
Adji Achmad Rinaldo FernandesUniversity of Brawijaya1
Nurjannah NurjannahUniversity of Brawijaya1
Yossy Maynaldi PratamaUniversity of Brawijaya1
Nabila Ayunda SoviaUniversity of Brawijaya1
Achmad EfendiUniversity of Brawijaya1
Candra R. W. S Weni UtomoUniversity of Brawijaya1
Maulidya MaghfiroUniversity of Brawijaya1
Suci AstutikUniversity of Brawijaya1
Nur Silviyah RahmiUniversity of Brawijaya1
Adinda Gita MaharaniUniversity of Brawijaya1
Atmadani Rahayu FakhrunnisaUniversity of Brawijaya1
Husnul KhatimahUniversity of Brawijaya1
Silvia Intan AuliaUniversity of Brawijaya1
Henny PramoedyoUniversity of Brawijaya1
Vita Dewi IslamiAffiliation 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.unnes.ac.id/journals/edaj/oai, first harvested 5 Nov 2026, last seen 5 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="en">Spatial Autocorrelation of East Java's Economic Growth Using Cluster-Based Weights</dc:title>
	<dc:creator xml:lang="en">Fitriani, Rahma</dc:creator>
	<dc:creator xml:lang="en">Wardhani, Ni Wayan Surya</dc:creator>
	<dc:creator xml:lang="en">Abdila, Naufal Shela</dc:creator>
	<dc:subject xml:lang="en">spatial weight matrix</dc:subject>
	<dc:subject xml:lang="en">spatial autocorrelation</dc:subject>
	<dc:subject xml:lang="en">spatial cluster</dc:subject>
	<dc:subject xml:lang="en">economic growth </dc:subject>
	<dc:description xml:lang="en">This study incorporates a spatial clustering technique into the formation of a spatial weight matrix as an alternative to the traditional exogenous matrix, aiming to better capture spatial dependencies. The approach is applied to analyze the spatial autocorrelation of economic growth in East Java’s regencies and municipalities using 2019–2021 data. Spatial clusters are identified based on GDP growth (GGDP), Human Development Index (HDI), population density (Dens), and geographical coordinates. These clusters are used to define a customized spatial weight matrix, where regions within the same cluster are designated as neighbors. Moran’s I, calculated using the customized spatial weight matrix, detects significant spatial autocorrelation in GDP growth for all three years, with consistently lower p-values compared to the traditional contiguity-based matrix. For example, in 2020, Moran’s I using the customized matrix yielded a p-value of 0.099 (significant at the 10% level), while the traditional matrix produced a non-significant p-value of 0.7965. These results demonstrate that spatial clustering extends the scope of spatial interaction beyond adjacent regions to include those with similar characteristics. The findings highlight the effectiveness of this method in providing a more nuanced and robust framework for analyzing spatial dependencies in economic growth.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2025-03-09</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">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/edaj/article/view/19161</dc:identifier>
	<dc:identifier>10.15294/edaj.v13i4.19161</dc:identifier>
	<dc:source xml:lang="en">Economics Development Analysis Journal; Vol. 13 No. 4 (2024): Economics Development Analysis Journal</dc:source>
	<dc:source>2502-2725</dc:source>
	<dc:source>2252-6560</dc:source>
	<dc:source>10.15294/edaj.v13i4</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/edaj/article/view/19161/3265</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Economics Development Analysis Journal</dc:rights>
</oai_dc:dc>