MENERAPKAN MODEL REGRESI POISSON PADA PENDUGAAN JUMLAH ANGKA KEMATIAN BAYI NEONATAL DI INDONESIA TAHUN 2022

HADIRINK, GHINA AURORA and Cahyawati S, Dian and Cahyono, Endro Setyo (2024) MENERAPKAN MODEL REGRESI POISSON PADA PENDUGAAN JUMLAH ANGKA KEMATIAN BAYI NEONATAL DI INDONESIA TAHUN 2022. Undergraduate thesis, Sriwijaya University.

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Abstract

This study aims to obtain a Poisson regression model for the number of neonatal mortality cases in Indonesia in 2022. The method used is Poisson regression analysis. The data were sourced from the website of Indonesian ministry of Health. The neonatal mortality data from Indonesia, covering 34 Provinces, include independent variables that are suspected factors influencing neonatal mortality. These independents variables are Low Birth Weight (LBW), Asphyxia, Neonatal tetanus, infection, congentinal abnormalities, and COVID-19. The result of the study provides a Poisson regression model for the number of neonatal mortality cases in Indonesia is λ_i=exp⁡〖(5,426-0,001838X_2-0,007973X_3+0,003739X_5-0,04256X_6)〗. Based on the obtained Poisson regression model, the variables asphyxia (X_2), noenatal tetanus 〖(X〗_3), congenital anomalies 〖(X〗_5), COVID-19 〖(X〗_6) are significant factors affecting neonatal mortality rates in Indonesia. The model indicates that as the incidence of Asphyxia, Neonatal tetanus and COVID-19 increases, the neonatal mortality rate decreases, conversely if the incidence of these factors decrease, the neonatal mortality rate increases. The model also shows that for each increase in the incidence of congentinal abnormalities, the neonatal mortality will rise, and similarity a decrease in these occurences will lead to a reduction in the neonatal mortality rate. Keywords: Asphyxia, Low Birth Weight (LBW),COVID-19, Poisson Regression, Neonatal Mortalityl.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Matematika, Regresi Poisson, kematian neonatal
Subjects:	Q Science > QA Mathematics > QA1-43 General
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Ghina Aurora Hadirink
Date Deposited:	25 Nov 2024 06:05
Last Modified:	25 Nov 2024 06:05
URI:	http://repository.unsri.ac.id/id/eprint/159778

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