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SISTEM INFORMASI GEOGRAFIS POTENSI EKONOMI DAERAH PROVINSI SULAWESI TENGGARA MENGGUNAKAN FUZZY C-MEANS CLUSTERING

SemanTIK: Teknik Informasi · Vol. 4 No. 1 (2018) · pp. 113–120

DOI
10.55679/semantik.v4i1.4037
ISSN
2502-8928, 2460-1446
Published
2018-07-12
Publisher
Informatics Engineering Department of Halu Oleo University
Language
eng

Abstract

Southeast Sulawesi Province consists of 15 districts and 2 cities. The economy of a region can be seen from the potentials that exist in the area. To obtain information on Regional Economic Potentials of Southeast Sulawesi Province can visit the Central Bureau of Statistics (BPS) of Southeast Sulawesi Province. Problems that occur usually people only get data numbers in the form of tables that are less informative so that less information can be caught.Therefore, to implement this application used Fuzzy C-Means Clustering method in grouping regional economic potential by utilizing Geographic Information System into a software.By using Fuzzy C-Means clustering to facilitate the clustering of an area with the largest, medium and low economic result and measure the accuracy level. The result is a visualization overview which shows the grouping of regions based on the economic results of Southeast Sulawesi.Keywords— Fuzzy C-means Clustering, GIS, Economic Potential.DOI: 10.5281/zenodo.1402840

Collaboration network of the authors

40 authors · 118 co-authorship links · 4 across different organisations · showing the 40 most connected

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

  • Universitas Halu Oleo
  • Institut Teknologi Sepuluh Nopember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Bambang PramonoUniversitas Halu Oleo7
Statiswaty StatiswatyUniversitas Halu Oleo5
Jumadil NangiUniversitas Halu Oleo4
LM. Fid AksaraUniversitas Halu Oleo3
Isnawaty IsnawatyAffiliation unknown3
Rahmat RamadhanUniversitas Halu Oleo3
Nur Fajriah MuchlisUniversitas Halu Oleo2
LM Bahtiar AksaraUniversitas Halu Oleo2
Ika Purwanti NingrumUniversitas Halu Oleo2
Natalis RansiUniversitas Halu Oleo2
Sari Fatiqah AyuAffiliation unknown2
Nike SyafitriUniversitas Halu Oleo2
Muh YaminUniversitas Halu Oleo2
Rizal Adi SaputraUniversitas Halu Oleo2
Lirna Frischa Dwi PutriAffiliation unknown1
Afriyadin AfriyadinAffiliation unknown1
Niarma NiarmaUniversitas Halu Oleo1
Mulatifa LalihaUniversitas Halu Oleo1
Rahmayunita RahmayunitaAffiliation unknown1
Yuwanda Purnamasari PasrunInstitut Teknologi Sepuluh Nopember1
Muh Iskandar Z. AAffiliation unknown1
Nur Arifah SyafitriAffiliation unknown1
Anita Puspita DewiAffiliation unknown1
Resti IdayaniAffiliation unknown1
Ramadhin ZaidUniversitas Halu Oleo1
Adnan HidayatUniversitas Halu Oleo1
Rosmila RosmilaAffiliation unknown1
Na’firul Hasna AriyaniAffiliation unknown1
Risna RisnaAffiliation unknown1
Sri Wayun WardaniAffiliation unknown1
Mutmainnah MuchtarInstitut Teknologi Sepuluh Nopember1
Annisyah JanuartiAffiliation unknown1
Muhammad HattaAffiliation unknown1
Adha Mashur SajiahUniversitas Halu Oleo1
Chindy Elfiana Suci NatasiyaAffiliation unknown1
Saskia Randawula SilondaeUniversitas Halu Oleo1
Edwin SaputraAffiliation 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://ojs.uho.ac.id/index.php/semantik/oai, first harvested 29 Oct 2026, last seen 29 Oct 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">SISTEM INFORMASI GEOGRAFIS POTENSI EKONOMI DAERAH PROVINSI SULAWESI TENGGARA MENGGUNAKAN FUZZY C-MEANS CLUSTERING</dc:title>
	<dc:creator>Wulan, Wa ode Sri</dc:creator>
	<dc:creator>Sutardi, Sutardi</dc:creator>
	<dc:creator>Tajidun, LM</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:description xml:lang="en-US">Southeast Sulawesi Province consists of 15 districts and 2 cities. The economy of a region can be seen from the potentials that exist in the area. To obtain information on Regional Economic Potentials of Southeast Sulawesi Province can visit the Central Bureau of Statistics (BPS) of Southeast Sulawesi Province. Problems that occur usually people only get data numbers in the form of tables that are less informative so that less information can be caught.Therefore, to implement this application used Fuzzy C-Means Clustering method in grouping regional economic potential by utilizing Geographic Information System into a software.By using Fuzzy C-Means clustering to facilitate the clustering of an area with the largest, medium and low economic result and measure the accuracy level. The result is a visualization overview which shows the grouping of regions based on the economic results of Southeast Sulawesi.Keywords— Fuzzy C-means Clustering, GIS, Economic Potential.DOI : 10.5281/zenodo.1402840</dc:description>
	<dc:publisher xml:lang="en-US">Informatics Engineering Department of Halu Oleo University</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2018-07-12</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://ojs.uho.ac.id/index.php/semantik/article/view/4037</dc:identifier>
	<dc:identifier>10.55679/semantik.v4i1.4037</dc:identifier>
	<dc:source xml:lang="en-US">SemanTIK : Teknik Informasi; Vol 4, No 1 (2018): semanTIK; 113-120</dc:source>
	<dc:source>2502-8928</dc:source>
	<dc:source>2460-1446</dc:source>
	<dc:source>10.55679/semantik.v4i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ojs.uho.ac.id/index.php/semantik/article/view/4037/3304</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2018 semanTIK</dc:rights>
</oai_dc:dc>