PEMODELAN JUMLAH KASUS KEMATIAN BAYI DI KABUPATEN KUANTAN SINGINGI MENGGUNAKAN REGRESI BINOMIAL NEGATIF

Simple item page
dc.contributor.authorSari, Luci Manda
dc.contributor.supervisorEfendi, Rustam
dc.date.accessioned2023-06-21T02:35:41Z
dc.date.available2023-06-21T02:35:41Z
dc.date.issued2023-04
dc.description.abstractInfant mortality is one of the commonly used mortality indicators in Indonesia. Cases of infant mortality reflect the level of social welfare and health status of a nation for the realization of health development in a country. One of the ways to reveal the high number of infant mortality cases is by knowing the most significant factors that cause infant mortality. The results obtained from this study experienced overdispersion in Poisson regression, so that in the analysis using negative binomial regression, a significant variable was obtained, namely the number of medical personnel with the best AIC in negative binomial regression for a significant variable in reduction II with an AIC value of 60.42en_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11031
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectInfant Mortality Casesen_US
dc.subjectPoisson Regressionen_US
dc.subjectOverdispersionen_US
dc.subjectNegative Binomal Regressionen_US
dc.titlePEMODELAN JUMLAH KASUS KEMATIAN BAYI DI KABUPATEN KUANTAN SINGINGI MENGGUNAKAN REGRESI BINOMIAL NEGATIFen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
LUCI MANDA SARI_compressed.pdf
Size:
223.36 KB
Format:
Unknown data format
Description:
artikel
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Mathematics