Widiawati, Nuzul (2023) Pemodelan Jumlah Kematian Ibu Dan Neonatal Di Jawa Timur Menggunakan Regresi Distribusi Diskrit. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
The number of maternal and neonatal mortality is one of the targets in Sustainable Development Goals (SDGs). The number of maternal Mortality is calculated from the period of pregnancy, childbirth, and postpartum but not due to other causes such as accidents or incidents. While neonatal mortality is the number of children born at a certain time and died at the time of neonatal age, which is 0-28 days. Maternal and neonatal mortality in Indonesia is still high, namely 4.627 maternal Mortality and 20.266 neonatal Mortality. East Java ranks second in maternal mortality and first in neonatal mortality. So there needs to be a solution to reduce the number of maternal and neonatal Mortality in East Java Province. Therefore, an analysis was carried out to determine the predictor variables thought to affect maternal and neonatal mortality in East Java using Discrete Distribution Regression. The results of the analysis show that the highest number of maternal deaths are in Tulungagung, Malang, Gresik, Mojokerto, Blitar and Jember districts. Meanwhile, the number of neonatal deaths was found in Jember Regency, Surabaya City and Kediri Regency. The method chosen for maternal and neonatal mortality cases in East Java is Generalized Poisson Regression. Variables that have a significant effect on maternal mortality are the percentage of deliveries by health personnel, the percentage of poor people, and the Human Development Index (IPM). Meanwhile, the predictor variables that have a significant effect on neonatal mortality are the number of puskesmas conducting classes for pregnant women, the percentage of deliveries by health personnel, Gross Domestic Product (GDP), and the Human Development Index (HDI). The research results can be used to evaluate and plan preventive programs in an effort to reduce maternal and neonatal mortality in East Java
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Jumlah kematian ibu dan neonatal merupakan salah satu target dalam pembangunan berkelanjutan atau Sustainable Development Goals (SDGs). Jumlah kematian ibu dihitung sejak periode kehamilan, persalinan, dan nifas tetapi bukan karena sebab lain seperti kecelakaan atau insidental. Sedangkan kematian neonatal adalah jumlah bayi yang dilahirkan pada waktu tertentu dan meninggal pada saat usia neonatal yaitu 0-28 hari. Kematian ibu dan neonatal di Indonesia masih tinggi yaitu 4.627 kematian ibu serta 20.266 kematian neonatal. Jawa Timur menduduki peringkat kedua kematian ibu dan peringkat pertama kematian neonatal. Sehingga perlu adanya solusi untuk menekan jumlah kematian ibu dan neonatal di Provinsi Jawa Timur. Oleh karena itu dilakukan analisis untuk mengetahui variabel prediktor yang diduga mempengaruhi kematian ibu dan neonatal di Provinsi Jawa Timur menggunakan Regresi Distribusi Diskrit. Hasil dari analisis menunjukkan bahwa kematian ibu terbanyak terdapat pada Kabupaten Tulungagung, Kabupaten Malang, Kabupaten Gresik, Kabupaten Mojokerto, Kabupaten Blitar, dan Kabupaten Jember. Sedangkan jumlah keamtian neonatal terdapat pada Kabupaten Jember, Kota Surabaya, dan Kabupaten Kediri. Metode yang terpilih pada kasus kematian ibu dan neonatal di Jawa Timur adalah Generalized Poisson Regression. Variabel yang berpengaruh signifikan terhadap kematian ibu adalah pesentase persalinan oleh tenaga kesehatan, persentase penduduk miskin, dan Indeks Pembangunan Manusia (IPM). Sedangkan variabel prediktor yang berpengaruh signifikan terhadap kematian neonatal adalah jumlah puskesmas yang melaksanakan kelas ibu hamil, pesentase persalinan oleh tenaga kesehatan, Produk Domestik Bruto (PDRB), dan Indeks Pembangunan Manusia (IPM). Hasil penelitian dapat digunakan untuk mengevaluasi serta merencanakan program preventif dalam upaya menurunkan angka kematian ibu dan neonatal di Provinsi Jawa Timur
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | Discrete Distribution Regression, Generalized Poisson Regression, Maternal Mortality, Neonatal Mortality, Generalized Poisson Regression, Kematian Ibu, Kematian Neonatal, Regresi Distribusi Diskrit, |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics |
Divisions: | Faculty of Vocational > 49501-Business Statistics |
Depositing User: | Nuzul Widiawati |
Date Deposited: | 28 Feb 2023 01:16 |
Last Modified: | 28 Feb 2023 01:16 |
URI: | http://repository.its.ac.id/id/eprint/97708 |
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