Melola Discovery

← Melola Discovery

Jurnal

Pendekatan Zero-Inflated Poisson Inverse Gaussian dalam Pemodelan Kasus Malaria di Puskesmas Kota Makassar

ESTIMASI: Journal of Statistics and Its Application · Vol. 6 No. 1 (2025) · pp. 101–115

DOI
10.70561/ejsa.v6i1.43164
ISSN
2721-379X, 2721-3803
Published
2025-02-17
Publisher
Hasanuddin University
Language
en

Abstract

Poisson regression is one of the approaches used to model count data. However, this method has an assumption of equidispersion that is not always met in actual data. One problem that often arises is overdispersion, especially when there are excess zeros in the dependent variable. The Mixed Poisson method, namely Zero-Inflated Poisson Inverse Gaussian (ZIPIG) regression is one approach that can be used when there is overdispersion in the data. Parameter estimation in the ZIPIG model is done using the Maximum Likelihood Estimation (MLE) method through Fisher Scoring Algorithm iterations. This study discusses how ZIPIG modeling is used to identify factors that influence the number of malaria cases in Makassar City Health Center in 2021. The results of the analysis show that the independent variables that have a significant effect on the number of malaria cases are the number of family heads with access to proper sanitation facilities (X1) and the presence of public places that meet health requirements (X2).

Keywords

Collaboration network of the authors

40 authors · 179 co-authorship links · showing the 40 most connected

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

  • Institut Agama Islam Negeri Kendari
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Anna IslamiyatiAffiliation unknown3
Nirwan IlyasAffiliation unknown3
Sitti SahrimanAffiliation unknown2
Muhammad FadilAffiliation unknown2
Anni Ivoni ParapaAffiliation unknown2
Siswanto SiswantoAffiliation unknown2
Zhazha Alifkhamulki RamdhaniAffiliation unknown1
Samsul ArifinAffiliation unknown1
Andi Sitti Fahmi Riyanti HufainiAffiliation unknown1
Dwicahyo Ramadhan PriyatnaAffiliation unknown1
La Podje TalangkoAffiliation unknown1
Vieri KoerniawanAffiliation unknown1
Nurtiti SunusiAffiliation unknown1
Dewi Rahma EnteAffiliation unknown1
Andi Kresna JayaAffiliation unknown1
Andi Tenri Riski AmaliaAffiliation unknown1
Fitri AnnisaAffiliation unknown1
Asnidar AsnidarAffiliation unknown1
Nurul HikmahInstitut Agama Islam Negeri Kendari1
Nasrah SirajangAffiliation unknown1
Andi Isna YunitaAffiliation unknown1
Rini JamalAffiliation unknown1
Andi M Alfin BasoAffiliation unknown1
Andi FebriyantiAffiliation unknown1
Rahmiati RahimAffiliation unknown1
Nurhaliza RaisAffiliation unknown1
Maryana MaharaniAffiliation unknown1
Rahmat HermawanAffiliation unknown1
Fadlan AminAffiliation unknown1
Ahmad Ryan Al AqshaAffiliation unknown1
Taufiqurrahman SadikinAffiliation unknown1
Nahdah Azatil IsmahAffiliation unknown1
RuslindaAffiliation unknown1
Najlah FauziahAffiliation unknown1
Azalia Filadelfia PagaloAffiliation unknown1
M. Zaky Hisyam GozhiAffiliation unknown1
Emha IsmaulidinAffiliation 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">Pendekatan Zero-Inflated Poisson Inverse Gaussian dalam Pemodelan Kasus Malaria di Puskesmas Kota Makassar</dc:title>
	<dc:creator xml:lang="en">Nurhidayah, Fauziah</dc:creator>
	<dc:creator xml:lang="en">Raupong, Raupong</dc:creator>
	<dc:creator xml:lang="en">Angriany, A.Muthiah Nur</dc:creator>
	<dc:subject xml:lang="en">Excess Zero</dc:subject>
	<dc:subject xml:lang="en">Malaria</dc:subject>
	<dc:subject xml:lang="en">Maximum Likelihood Estimation</dc:subject>
	<dc:subject xml:lang="en">Overdispersi</dc:subject>
	<dc:subject xml:lang="en">Zero-Inflated Poisson</dc:subject>
	<dc:description xml:lang="en">Poisson regression is one of the approaches used to model count data. However, this method has an assumption of equidispersion that is not always met in actual data. One problem that often arises is overdispersion, especially when there are excess zeros in the dependent variable. The Mixed Poisson method, namely Zero-Inflated Poisson Inverse Gaussian (ZIPIG) regression is one approach that can be used when there is overdispersion in the data.  Parameter estimation in the ZIPIG model is done using the Maximum Likelihood Estimation (MLE) method through Fisher Scoring Algorithm iterations. This study discusses how ZIPIG modeling is used to identify factors that influence the number of malaria cases in Makassar City Health Center in 2021. The results of the analysis show that the independent variables that have a significant effect on the number of malaria cases are the number of family heads with access to proper sanitation facilities (X1) and the presence of public places that meet health requirements  (X2).</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2025-02-17</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/43164</dc:identifier>
	<dc:identifier>10.70561/ejsa.v6i1.43164</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 6, No. 1, Januari, 2025 : Estimasi; 101-115</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/43164/12563</dc:relation>
</oai_dc:dc>