PENERAPAN GENERALIZED RIDGE REGRESSION DENGAN MM-ESTIMATION PADA ANGKA KEMATIAN BAYI DI JAWA TIMUR

AMIRA BASYILA SARWA, . (2025) PENERAPAN GENERALIZED RIDGE REGRESSION DENGAN MM-ESTIMATION PADA ANGKA KEMATIAN BAYI DI JAWA TIMUR. Sarjana thesis, UNIVERSITAS NEGERI JAKARTA.

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Abstract

Bayi termasuk kelompok yang memerlukan perhatian khusus di sektor kesehatan dan berperan penting dalam pencapaian Target 3.2 SDGs. Kematian bayi masih menjadi masalah kesehatan yang serius di banyak negara, termasuk Indonesia. Di Indonesia, Angka Kematian Bayi (AKB) di Provinsi Jawa Timur masih jauh dibawah target SDGs. Banyak faktor yang memengaruhi AKB, namun antar faktor sering kali berkorelasi serta adanya pencilan pada amatan sehingga tujuan penelitian ini adalah untuk menganalisis faktor yang memengaruhi AKB di Provinsi Jawa Timur menggunakan Generalized Ridge Regression dengan MM-Estimation (GRR – MM). Penelitian ini menggunakan data sekunder yang bersumber dari Badan Pusat Statistik dan Dinas Kesehatan. Variabel pada penelitian ini terdiri dari satu variabel respon dengan 13 variabel prediktor. Unit amatannya sebanyak 38 amatan, dengan 29 kabupaten dan 9 kota. Berdasarkan nilai R-squared (90,13%), R-squared adjusted (84,78%), AIC (125,053), dan BIC (149,617) didapatkan bahwa model GRR – MM merupakan model terbaik dibandingkan regresi linier berganda (OLS) maupun regresi robust (MM-Estimation). Berdasarkan model GRR – MM, terdapat lima faktor yang berpengaruh secara signifikan terhadap AKB di Provinsi Jawa Timur, yaitu Persentase Bayi Berat Badan Lahir Rendah (X1), Rata-rata Lamanya Bayi Diberi ASI Eksklusif (X2), Persentase Rumah Tangga Memiliki Akses Sanitasi Layak (X9), Rata-rata Lama Sekolah Perempuan (X10), dan Tingkat Pengangguran Terbuka (X13). ***** Infants are a group that requires special attention in the health sector and plays an important role in achieving SDG Target 3.2. Infant mortality remains a serious health problem in many countries, including Indonesia. In Indonesia, the Infant Mortality Rate (IMR) in East Java Province is still far below the SDG target. Many factors influence the IMR, but these factors are often correlated to each other, and there are outliers in the observations. Therefore, the objective of this study is to analyze the factors influencing the IMR in East Java Province using Generalized Ridge Regression with MM-Estimation (GRR – MM). This study uses secondary data sourced from the Central Statistics Bureau and the Health Department. The variables in this study consist of one response variable with 13 predictor variables. The sample size is 38 observations, comprising 29 districts and 9 cities. Based on the R-squared value (90,13%), adjusted R-squared (84,78%), AIC (125,053), and BIC (149,617), it was found that the GRR – MM model is the best model compared to multiple linear regression (OLS) and robust regression (MM-Estimation). Based on the GRR-MM model, there are five factors that significantly influence AKB in East Java Province, namely the percentage of low birth weight infants (X1), the average duration of exclusive breastfeeding (X2), Percentage of Households with Access to Adequate Sanitation (X9), Average Length of Schooling for Women (X10), and Unemployment Rate (X13).

Item Type: Thesis (Sarjana)
Additional Information: 1). Dr. Vera Maya Santi, S.Si., M.Si. ; 2). Prof. Dr. Ir. Bagus Sumargo, M.Si.
Subjects: Sains > Statistika
Divisions: FMIPA > S1 Statistika
Depositing User: Amira Basyila Sarwa .
Date Deposited: 17 Nov 2025 02:23
Last Modified: 17 Nov 2025 02:23
URI: http://repository.unj.ac.id/id/eprint/62814

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