Yumna, Adinda Alifia (2024) Pemodelan Faktor-Faktor yang Berpengaruh Terhadap Jumlah Kematian Maternal dan Neonatal di Kabupaten Jember dengan Bivariate Generalized Poisson Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kematian maternal dan neonatal saling terkait. Hal ini dikarenakan selama masa kehamilan, bayi mengandalkan asupan nutrisi dari ibu melalui plasenta. Kesehatan ibu saat hamil berdampak langsung pada perkembangan janin yang akan lahir. Jumlah kematian maternal dan neonatal merupakan dua indikator penting dalam mengevaluasi kualitas fasilitas kesehatan masyarakat, khususnya pada area kesehatan keluarga. Kedua variabel tersebut dapat dipandang sebagai dua variabel random yang saling berkorelasi. Pentingnya untuk menginvestigasi faktor-faktor yang memengaruhi kedua fenomena ini semakin mendesak, karena tingginya jumlah kematian maternal dan neonatal di beberapa wilayah di Indonesia masih jauh melampaui target sustainable development goals (SDGs), salah satunya terjadi di Kabupaten Jember. Kabupaten Jember memiliki jumlah kematian maternal dan neonatal yang paling tinggi di Provinsi Jawa Timur pada tahun 2022. Penelitian ini menggunakan pemodelan bivariate generalized Poisson regression (BGPR) untuk mengidentifikasi faktor-faktor yang diduga memengaruhi jumlah kematian maternal dan neonatal di Kabupaten Jember. Metode BGPR dipilih karena kemampuannya dalam menganalisis keterkaitan antara variabel cacahan yang mengalami overdispersi. Hasil pemodelan menunjukkan bahwa variabel-variabel, seperti persentase kunjungan ibu hamil K1, persentase kunjungan ibu hamil K4, persentase ibu hamil bersalin di fasilitas pelayanan kesehatan (fasyankes), persentase kunjungan ibu nifas (KF) mendapat vitamin A, persentase ibu hamil mendapat imunisasi Td2+, persentase ibu hamil mengonsumsi tablet tambah darah (TTD), dan persentase ibu hamil mengalami komplikasi kebidanan ditangani (komkeb) berpengaruh signifikan terhadap jumlah kematian maternal, sedangkan persentase kunjungan ibu hamil K1, dan persentase kunjungan ibu hamil K4 berpengaruh signifikan terhadap jumlah kematian neonatal.
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Maternal and neonatal deaths are interrelated. This is because during pregnancy, the baby relies on nutritional intake from the mother through the placenta. Maternal health during pregnancy directly impacts the development of the unborn fetus. The number of maternal and neonatal deaths are two important indicators in evaluating the quality of public health facilities, particularly in family health areas. These two variables can be viewed as two random variables that are correlated. The importance of investigating the factors affecting these phenomena is increasingly urgent, as the high number of maternal and neonatal deaths in some regions of Indonesia still far exceeds the targets of the sustainable development goals (SDGs), with one such case occurring in Kabupaten Jember. Kabupaten Jember had the highest number of maternal and neonatal deaths in East Java Province in 2022. This study uses bivariate generalized Poisson regression (BGPR) modeling to identify factors that are suspected to influence the number of maternal and neonatal deaths in Kabupaten Jember. The BGPR method was chosen due to its ability to analyze the correlation between count variables experiencing overdispersion. The modeling results indicate that variables such as the percentage of K1 antenatal care visits, the percentage of K4 antenatal care visits, the percentage of deliveries at healthcare facilities, the percentage of postpartum visits receiving vitamin A, the percentage of pregnant women receiving Td2+ immunization, the percentage of pregnant women consuming iron tablets, and the percentage of pregnant women experiencing managed obstetric complications have a significant impact on the number of maternal deaths, while the percentage of K1 antenatal care visits and the percentage of K4 antenatal care visits significantly affect the number of neonatal deaths.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Bivariate Generalized Poisson Regression, Kematian Maternal, Kematian Neonatal, Sustainable Development Goals, Bivariate Generalized Poisson Regression, Maternal Mortality, Neonatal Mortality, Sustainable Development Goals |
| Subjects: | H Social Sciences > HA Statistics > HA31.3 Regression. Correlation |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Adinda Alifia Yumna |
| Date Deposited: | 09 Aug 2024 06:40 |
| Last Modified: | 09 Aug 2024 06:40 |
| URI: | http://repository.its.ac.id/id/eprint/114979 |
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