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Improvement Method of Fuzzy Geographically Weighted Clustering using Gravitational Search Algorithm

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 11 No. 1 (2018) · pp. 10–16

DOI
10.21609/jiki.v11i1.580
ISSN
2502-9274, 2088-7051
Published
2018-02-28
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Geo-demographic analysis (GDA) is a useful method to analyze information based on location, utilizing several spatial analysis explicitly. One of the most efficient and commonly used method is Fuzzy Geographically Weighted Clustering (FGWC). However, it has a limitation in obtaining local optimal solution in the centroid initialization. A novel approach integrating Gravitational Search Algorithm (GSA) with FGWC is proposed to obtain global optimal solution leading to better cluster quality. Several cluster validity indexes are used to compare the proposed methods with the FGWC using other optimization approaches. The study shows that the hybrid method FGWC-GSA provides better cluster quality. Furthermore, the method has been implemented in R package spatialClust.

Keywords

Collaboration network of the authors

2 authors · 1 co-authorship link · 1 across different organisations

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  • Karolinska Institutet
  • Badan Pusat Statistik
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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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://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Improvement Method of Fuzzy Geographically Weighted Clustering using Gravitational Search Algorithm</dc:title>
	<dc:creator>Pramana, Setia</dc:creator>
	<dc:creator>Pamungkas, Imam Habib</dc:creator>
	<dc:subject xml:lang="en-US">clustering</dc:subject>
	<dc:subject xml:lang="en-US">Fuzzy Geographically Weighted Clustering (FGWC)</dc:subject>
	<dc:subject xml:lang="en-US">Gravitational Search Algorithm (GSA)</dc:subject>
	<dc:description xml:lang="en-US">Geo-demographic analysis (GDA) is a useful method to analyze information based on location, utilizing several spatial analysis explicitly. One of the most efficient and commonly used method is Fuzzy Geographically Weighted Clustering (FGWC).  However, it has a limitation in obtaining local optimal solution in the centroid initialization. A novel approach integrating Gravitational Search Algorithm (GSA) with FGWC is proposed to obtain global optimal solution leading to better cluster quality. Several cluster validity indexes are used to compare the proposed methods with the FGWC using other optimization approaches. The study shows that the hybrid method FGWC-GSA provides better cluster quality. Furthermore, the method has been implemented in R package spatialClust.</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2018-02-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/580</dc:identifier>
	<dc:identifier>10.21609/jiki.v11i1.580</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 11 No. 1 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 10-16</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v11i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/580/388</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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