Fitriani, Devi Nur (2024) Analisis Faktor-Faktor yang Mempengaruhi Jumlah Kematian Ibu di Provinsi Sumatera Utara dengan Metode Generalized Poisson Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kematian ibu merupakan salah satu permasalahan yang menjadi fokus utama di bidang kesehatan. Berbagai upaya diciptakan sebagai strategi untuk menekan jumlah kematian ibu di Indonesia. Namun demikian, hingga saat ini jumlah kematian ibu di beberapa provinsi di Indonesia masih tinggi, salah satunya di peringat ke tujuh dengan jumlah kematian ibu tertinggi adalah Provinsi Sumatera Utara. Pada tahun 2022 jumlah kematian ibu di Sumatera Utara mencapai 131 jiwa. Metode yang dapat digunakan untuk mengetahui faktor-faktor yang mempengatuhi jumlah kematian ibu adalah Generalized Poisson Regression (GPR). Metode GPR berfungsi mengatasi overdispersi pada regresi poisson, sehingga model yang didapatkan akan lebih akurat. Pemodelan terbaik yang didapatkan dari kriteria AIC minimum menghasilkan tiga variabel prediktor yang berpengaruh terhadap variabel jumlah kematian ibu di Sumatera Utara tahun 2022. Hasil yang didapatkan menunjukkan bahwa faktor yang berpengaruh secara signifikan terhadap jumlah kematian ibu di Sumatera Utara tahun 2022 adalah persentase kunjungan ibu hamil (K4), persentase penduduk miskin, dan jumlah Keluarga Penerima Manfaat (KPM).
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Mother's death is one of the major health issues in the health sector. Various efforts and policies are being pursued as a form of strategy to suppress the number of maternal deaths in Indonesia. Nevertheless, to date, the number of maternal deaths in some provinces in Indonesia is still high, one of the seven highest in memory, is the Province of North Sumatra. By 2022, the number of mother deaths in Province of North Sumatra reached 131. Generalized Poisson Regression (GPR) is a method that can be used to determine factors that match the number of maternal deaths. The GPR method works to address overdispersion on poisson regression, so the model obtained will be more accurate. The best model obtained from the AIC minimum criteria produces three predictor variables that affect the variable of the number of maternal deaths. The results show that the factors that significantly influence maternal deaths in North Sumatra by 2022 are the percentage of pregnant women visiting (K4), the proportion of the poor population, and the number of beneficiary families (KPM).
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | Generalized Poisson Regression, Kematian Ibu, Overdispersi, Sumatera Utara, Regresi Poisson, GPR, Mother’s Death , North Sumatera, Overdispersion, Poisson Regression |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics H Social Sciences > HA Statistics > HA31.3 Regression. Correlation H Social Sciences > HA Statistics > HA31.7 Estimation H Social Sciences > HQ The family. Marriage. Woman R Medicine > RA Public aspects of medicine > RA971 Health services administration. |
Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
Depositing User: | Devi Nur Fitriani |
Date Deposited: | 09 Aug 2024 02:04 |
Last Modified: | 09 Aug 2024 02:04 |
URI: | http://repository.its.ac.id/id/eprint/115025 |
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