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Pemodelan Kasus Kematian Demam Berdarah Dengue di Provinsi Sulawesi Selatan dengan Menggunakan Model GWZIPR

ESTIMASI: Journal of Statistics and Its Application · Vol. 7 No. 1 (2026) · pp. 1–11

DOI
10.20956/ejsa.v7i1.25215
ISSN
2721-379X, 2721-3803
Published
2026-05-05
Publisher
Hasanuddin University
Language
en

Abstract

Dengue Hemorrhagic Fever (DHF) has spread widely throughout the region with the number of districts/cities being infected increasing to remote areas. Data on the spread or death rate from DHF in certain locations includes spatial data. The number of deaths due to DHF cases in South Sulawesi in 2019 contained 66.67% zero value, so the Geographically Weighted Zero Inflated Poisson Regression (GWZIPR) model was used to deal with spatial data that contains many zero-value observations. Based on the simultaneous test, it was found that the GWZIPR model was feasible to use with a deviation value of 100.1557. Districts/cities in South Sulawesi have various significant variables due to spatial variations between observations and areas that are closer give greater weight so that several districts/cities have the same significant variables. In the GWZIPR model with adaptive bisquare kernel weights, the variables that affect DHF mortality in all districts/cities are the percentage of drinking water facilities that meet health requirements and population density.

Keywords

Collaboration network of the authors

40 authors · 106 co-authorship links · showing the 40 most connected

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  • Sultan Ageng Tirtayasa University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anisa AnisaSultan Ageng Tirtayasa University7
Raupong RaupongAffiliation unknown6
Sri Astuti ThamrinAffiliation unknown3
Nirwan IlyasAffiliation unknown3
La Podje TalangkoAffiliation unknown2
Muhammad Jayzul UsrahAffiliation unknown2
Anisa KalondengAffiliation unknown2
Sitti SahrimanAffiliation unknown2
Nurtiti SunusiAffiliation unknown2
Nasrah SirajangAffiliation unknown2
Siswanto SiswantoAffiliation unknown2
Widya Nauli Amalia PuteriAffiliation unknown1
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Bunga ApriliaAffiliation unknown1
Rusydah KhaeratiAffiliation unknown1
Grace Oktavia YusufAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Fitriatusakiah FitriatusakiahAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
AnisaAffiliation unknown1
Georgina Maria TinungkiAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Novilia JaoAffiliation unknown1
Najiha AlimatunAffiliation unknown1
Reski AmalahAffiliation unknown1
Ainun Utari BudistiharahAffiliation unknown1
Mamik UtamiAffiliation unknown1
Fitri FitriAffiliation unknown1
Nur Fuadil Maqnun WahabAffiliation unknown1
Nurtit SunusiAffiliation unknown1
Ainul FajriAffiliation unknown1
Anisa Haura Salsa Fatih YusufAffiliation unknown1
Ika Pratiwi HayaAffiliation unknown1
Hajratul Ashwad KAffiliation unknown1
Wa Ode Sitti Amni AmniAffiliation unknown1
Amalia AndrianingrumAffiliation 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.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 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">Pemodelan Kasus Kematian Demam Berdarah Dengue di Provinsi Sulawesi Selatan dengan Menggunakan  Model GWZIPR</dc:title>
	<dc:creator xml:lang="en">Aicha, Andi Ummi Melin Aicha</dc:creator>
	<dc:creator xml:lang="en">Islamiyati, Anna</dc:creator>
	<dc:creator xml:lang="en">Jaya, Andi Kresna</dc:creator>
	<dc:subject xml:lang="en">DHF</dc:subject>
	<dc:subject xml:lang="en">GWZIPR</dc:subject>
	<dc:subject xml:lang="en">Adaptive Bisquare</dc:subject>
	<dc:subject xml:lang="en">Kernel</dc:subject>
	<dc:subject xml:lang="en">South Sulawesi</dc:subject>
	<dc:description xml:lang="en">Dengue Hemorrhagic Fever (DHF) has spread widely throughout the region with the number of districts/cities being infected increasing to remote areas. Data on the spread or death rate from DHF in certain locations includes spatial data. The number of deaths due to DHF cases in South Sulawesi in 2019 contained 66.67% zero value, so the Geographically Weighted Zero Inflated Poisson Regression (GWZIPR) model was used to deal with spatial data that contains many zero-value observations. Based on the simultaneous test, it was found that the GWZIPR model was feasible to use with a deviation value of 100.1557. Districts/cities in South Sulawesi have various significant variables due to spatial variations between observations and areas that are closer give greater weight so that several districts/cities have the same significant variables. In the GWZIPR model with adaptive bisquare kernel weights, the variables that affect DHF mortality in all districts/cities are the percentage of drinking water facilities that meet health requirements and population density.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2026-05-05</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://journal.unhas.ac.id/index.php/ESTIMASI/article/view/25215</dc:identifier>
	<dc:identifier>10.20956/ejsa.v7i1.25215</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 7, No. 1, Januari, 2026 : Estimasi; 1-11</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/25215/14378</dc:relation>
</oai_dc:dc>