Aminullah, Affanda Abdul Hakim (2019) Pemodelan Untuk Jumlah Kasus Kematian Bayi dan Ibu di Jawa Timur Menggunakan Bivariate Generalized Poisson Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
06211745000018-Undergraduate_Theses.pdf - Published Version Download (3MB) | Preview |
Abstract
Angka kematian bayi (AKB) dan angka kematian ibu (AKI) merupakan salah satu indikator penting dalam menentukan tingkat kesehatan dan keberhasilan pembangunan di suatu wilayah. Angka kematian bayi dan ibu baru lahir di Jatim masih tinggi, saat ini Jawa Timur belum mampu mencapai target SDGs pada angka kematian bayi dan ibu yaitu sebesar 70/100.000 kelahiran sedangkan Jawa Timur masih 90/100.000 kelahiran. Penelitian ini menggunakan metode Bivariate Generalized Poisson Regression untuk melihat faktor-faktor yang mempengaruhi jumlah kasus kematian bayi dan ibu di Jawa Timur tahun 2017. Bivariate Generalized Poisson Regression merupakan salah satu metode untuk menanggulangi kasus overdispersi data. Berdasarkan hasil analisis Bivariate Generalized Poisson Regression dengan kriteria AICc diketahui bahwa model terbaik memuat keseluruhan variabel prediktor. Faktor yang mempengaruhi jumlah kematian bayi di Jawa Timur tahun 2017 adalah persentase persalinan oleh tenaga kesehatan, persentase komplikasi kebidanan yang ditangani, persentase kunjungan ibu hamil dengan K4, persentase ibu hamil mendapat tablet Fe3, sedangkan variabel predictor yang berpengaruh untuk jumlah kematian ibu di Jawa Timur tahun 2017 adalah persentase persalinan oleh tenaga kesehatan, persentase rumah tangga ber-PHBS.
==============================================================================================================================
The infant mortality rate (IMR) and maternal mortality rate (MMR) is one of the important indicators in determining the level of health and the success of development in a region. IMR and MMR in East Java are still high, currently East Java has not been able to reach SDGs based on the infant and maternal mortality rate of 70 / 100,000 East Java births, still 90 / 100,000 births. This study uses the Poisson Generalized Bivariate Regression method to look at the factors that influence the number of infant and maternal deaths in East Java in 2017. Poisson Generalized Bivariate regression is one method for overcoming data overdispersion cases. Based on the results of the analysis of Generic Poisson Bivariate Regression with the AICc criteria which is called the best predictor model. Factors that influence the number of infant deaths in East Java in 2017 are the percentage of births by health workers, the percentage of obstetric difficulties that support, the percentage of visits of pregnant women with K4, the percentage of pregnant women receiving Fe3 tablets, while the predictor variables associated with the number of mothers in East Java 2017 is the percentage of deliveries by health workers, the percentage of clean and healthy living.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.536 Ami p-1 2019 |
| Uncontrolled Keywords: | AICc, Bivariate Generalized Poisson Regression, AKB, AKI, Overdispersi |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Aminullah Affanda Abdul Hakim |
| Date Deposited: | 27 Dec 2022 03:01 |
| Last Modified: | 27 Dec 2022 03:01 |
| URI: | http://repository.its.ac.id/id/eprint/63758 |
Actions (login required)
 |
View Item |