Pemodelan Jumlah Kematian Bayi Dengan Pendekatan Geographically Weighted Poisson Regression Semiparametric Di Propinsi Jawa Timur Pada Tahun 2009

Hakim, Ahmad Faisol (2011) Pemodelan Jumlah Kematian Bayi Dengan Pendekatan Geographically Weighted Poisson Regression Semiparametric Di Propinsi Jawa Timur Pada Tahun 2009. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 1307030039-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (6MB) | Request a copy

Abstract

Jumlah kematian bayi merupakan indikator yang penting untuk mengukur keadaan tingkat kesehatan di suatu masyarakat. Pada tahun 2009, jumlah kematian bayi mencapai 38,9 per 1000 kelahiran hidup. 0leh karena itu, perlu dilakukan pene/itian untuk mendapatkan model terbaik dan faktor-faktor yang mempengaruhi jumlah kematian bayi di Propinsi Jawa Timur. Analisis yang dilakukan yaitu dengan pendekatan Geographically Weighted Poisson Regression Semiparametric (GWPRS) merupakan perluasan dari model Geographically Weighted Poisson Regression (GWPR) yang merupakan bentuk lokal dari regresi Poisson dimana lokasi diperhatikan dan diasumsikan data berdistribusi Poisson. Hasil analisis menunjukkan bahwa variabel yang berpengaruh signifikan terhadap jumlah kematian bayi di seluruh kabupaten/Kota di Propinsi Jawa Timur Tahun 2009 adalah Jumlah tenaga medis (X2Y. Sedangkan faktor-faktor lain yang mempe-ngaruhi jumlah kematian bayi adalah Jumlah sarana kesehatan (X1), Persentase persalinan yang dilakukan dengan bantuan non medis (dukun bayi) (X1) , Rata-rata usia perkawinan perlama (X4) , Rata-rata lama sekolah wanita berstatus kawin (X5), Rataratajumlah pengeluaran rumah tangga (dalam rupiah) (Xr), Persentase daerah yang ber-status desa (X7), Rata-rata lama pemberian AS/eksklusif (X,J, Persen-tase rumah tangga yang memiliki air bersih (X9) , dan Persentase pendu-duk miskin (X11J). Model yang lebih baik digunakan untuk menganalisa data jumlah kematian bayi di tiap Kabupaten/Kota di Propinsi Jawa Timur Tahun 2009 adalah model GWPR karena memiliki nilai A/C yang terkecil dibandingkan dengan model Regresi Poisson dan GWPRS
====================================================================================================================================
The number of infant deaths is an important indicator for measuring the level of health in a community. In 2009, the number of infant deaths reached 38.9 per 1,000 live births. Therefore, research is needed to obtain the best model and factors that influence the number of infant deaths in East Java Province. The analysis carried out was the Geographically Weighted Poisson Regression Semiparametric (GWPRS) approach, an extension of the Geographically Weighted Poisson Regression (GWPR) model, which is a local form of Poisson regression where location is considered and the data is assumed to be distributed Poisson. The results of the analysis show that the variables that significantly influence the number of infant deaths in all districts/cities in East Java Province in 2009 are the number of medical personnel (X2Y). Meanwhile, other factors that influence the number of infant deaths are the number of health facilities (X1), the percentage of deliveries carried out with non-medical assistance (traditional midwives) (X1), the average age of marriage (X4), the average length of schooling of married women (X5), the average amount of household expenditure (in rupiah) (Xr), the percentage of areas with village status (X7), the average length of time given AS/exclusive breastfeeding (X,J), the percentage of households with clean water (X9), and the percentage of poor population (X11J). The better model used to analyze the data on the number of infant deaths in each district/city in East Java Province in 2009 is the GWPR model because it has the smallest A/C value compared to the Poisson Regression and GWPRS models

Item Type:	Thesis (Other)
Additional Information:	RSSt 519.536 Hak p-1 2011 (weding)
Uncontrolled Keywords:	Regresi Poisson, GWPR, GWPRS, AIC, Jumlah kematian bayi; Poisson regression, GWPR, GWPRS, AIC, infant mortality rate (IMR)
Subjects:	H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
Divisions:	Faculty of Mathematics and Science > Statistics > 49401-(D3) Diploma 3
Depositing User:	EKO BUDI RAHARJO
Date Deposited:	21 Aug 2025 08:04
Last Modified:	21 Aug 2025 08:04
URI:	http://repository.its.ac.id/id/eprint/128156

Actions (login required)

View Item