Adryanta, Muhamad (2019) Analisis Metode Geographically Weighted Generalized Poisson Regression untuk Pemodelan Faktor yang Mempengaruhi Jumlah Kematian Anak di Provinsi Jawa Timur. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Jumlah kematian anak merupakan permasalahan dari salah satu tujuan dalam Sustainable Development Goals (SDGs), yaitu menjamin hidup sehat untuk seluruh penduduk dunia di segala umur. Penelitian ini melakukan analisis jumlah kematian anak di Provinsi Jawa Timur pada tahun 2017 beserta faktor-faktor yang diduga mempengaruhinya dengan menggunakan metode Geographically Weighted Generalized Poisson Regression (GWGPR) karena adanya faktor spasial yaitu antar kabupaten/kota. Hasil pemodelan GWGPR tanpa exposure diketahui menghasilkan dua kelompok kabupaten/kota dengan variabel yang berpengaruh signifikan antara lain persentase rumah tangga ber-PHBS, persentase rumah sehat, persentase penduduk dengan akses terhadap fasilitas sanitasi yang layak (jamban sehat), persentase desa/kelurahan yang melaksanakan sanitasi total berbasis masyarakat, penduduk dengan akses berkelanjutan terhadap air minum berkualitas (layak), dan persentase penduduk miskin. Sementara pemodelan GWGPR dengan menggunakan exposure diketahui tidak ada satupun faktor yang berpengaruh secara signifikan.
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The number of child mortality is about problem from one of the goals in the Sustainable Development Goals (SDGs), which guarantees a healthy life for all the world’s population at all ages. This research analyzed the number of child mortality in East Java Province at 2017 along with the factors suspected influencing them using Geographically Weighted Generalized Poisson Regression (GWGPR) method associated to the presence of spatial factors (districts or cities). GWGPR modeling results without exposure are known resulting two groups of districts / cities with variables that significantly influence the percentage of households with PHBS (clean behavior of healthy living), percentage of healthy houses, percentage of residents with access to proper sanitation facilities (healthy latrines), percentage of villages implementing community-based total sanitation, residents with sustainable access to quality (proper) drinking water, and the percentage of poor people. While GWGPR modeling using exposure is known no single factor that has a significant effect.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.536 Adr a-1 2019 |
| Uncontrolled Keywords: | Exposure, GWGPR, Kematian Anak, Spasial |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | ADRYANTA MUHAMAD |
| Date Deposited: | 06 Jun 2023 06:20 |
| Last Modified: | 06 Jun 2023 06:23 |
| URI: | http://repository.its.ac.id/id/eprint/63959 |
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