Pemodelan Angka Kematian Ibu di Provinsi Jawa Timur Menggunakan Geographically Weighted Regression

Muflihan, Raihan (2025) Pemodelan Angka Kematian Ibu di Provinsi Jawa Timur Menggunakan Geographically Weighted Regression. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Angka Kematian Ibu (AKI) merupakan indikator utama kesehatan ibu dan anak serta menjadi target Sustainable Development Goals (SDGs). Jawa Timur menghadapi tantangan besar dalam menurunkan AKI akibat keragaman geografis, sosial ekonomi, dan rendahnya tingkat pendidikan di beberapa kabupaten. Selain melebihi target SDGs, beberapa wilayah di provinsi ini memiliki AKI yang melampaui batas darurat. Untuk menganalisis faktor lokal yang memengaruhi AKI, penelitian ini menggunakan metode Geographically Weighted Regression (GWR) yang mempertimbangkan variasi spasial antar wilayah. Hasil penelitian menunjukkan bahwa metode Geographically Weighted Regression (GWR) menghasilkan model yang lebih akurat dibandingkan metode regresi linear berganda. Hal ini ditunjukkan oleh nilai Sum of Squared Errors (SSE) yang lebih kecil dan nilai R-squared yang lebih tinggi dibandingkan regresi linear berganda. Analisis GWR juga mengidentifikasi bahwa hubungan antara variabel-variabel signifikan terhadap AKI bervariasi antar kabupaten/kota. Semua variabel prediktor yang digunakan, yaitu prevalensi ketidakcukupan pangan, persentase ibu hamil yang mengikuti program K6, persentase ibu hamil yang menerima imunisasi Td2+, persentase ibu hamil dengan komplikasi kebidanan yang ditangani, dan Indeks Pembangunan Gender, terbukti signifikan setidaknya di lebih dari satu kabupaten/kota. Hasil penelitian menghasilkan 11 kelompok kabupaten/kota berdasarkan kesamaan variabel yang signifikan terhadap AKI. Mayoritas kabupaten/kota dalam satu kelompok berada berdekatan secara geografis, menunjukkan adanya pengaruh lokal dari faktor-faktor tersebut. Temuan ini memberikan wawasan mendalam mengenai distribusi spasial AKI di Jawa Timur, sehingga dapat digunakan untuk memprioritaskan kebijakan intervensi yang lebih efektif. Dengan memahami faktor-faktor lokal yang berkontribusi, pendekatan berbasis bukti dapat diterapkan untuk mendukung upaya penurunan AKI secara signifikan menuju pencapaian target pembangunan berkelanjutan.
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Maternal Mortality Rate (MMR) is a key indicator of maternal and child health and is one of the targets of the Sustainable Development Goals (SDGs). East Java faces significant challenges in reducing MMR due to geographic diversity, socioeconomic disparities, and low education levels in several districts. In addition to exceeding the SDG target, some areas in this province have MMR rates that surpass the emergency threshold. To analyze local factors influencing MMR, this study employs the Geographically Weighted Regression (GWR) method, which accounts for spatial variation between regions. The results demonstrate that the GWR method produces a more accurate model compared to multiple linear regression, as indicated by a lower Sum of Squared Errors (SSE) and a higher R-squared value. The GWR analysis also identifies that the influence between significant variables and MMR varies across districts or cities. All predictor variables used such as prevalence of food insufficiency, percentage of pregnant women participating in the K6 program, percentage of pregnant women receiving Td2+ immunization, percentage of pregnant women with obstetric complications receiving treatment, and the Gender Development Index proved to be significant in at least one district or city. The study results classify 11 groups of districts or cities based on similarities in significant variables affecting MMR. Most districts or cities within the same group are geographically close, indicating local influences of these factors. These findings provide deeper insights into the spatial distribution of MMR in East Java, offering valuable guidance for prioritizing more effective intervention policies. By understanding the local factors contributing to MMR, evidence-based approaches can be applied to support efforts in significantly reducing MMR toward achieving sustainable development goals.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Maternal Mortality Rate, Geographically Weighted Regression, East Java, AKI, Geographically Weighted Regression, Provinsi Jawa Timur
Subjects:	H Social Sciences > HA Statistics > HA30.6 Spatial analysis H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis.
Divisions:	Faculty of Vocational > 49501-Business Statistics
Depositing User:	Raihan Muflihan
Date Deposited:	24 Jan 2025 04:08
Last Modified:	24 Jan 2025 04:08
URI:	http://repository.its.ac.id/id/eprint/116796

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