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Puspitasari, Dwi Ajeng
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Pemodelan Geographically Weighted Regression (GWR) dalam Prevalensi Obesitas Dewasa Kabupaten/Kota di Indonesia Tahun 2018 Prana, Fadhil Aqsa; Khairunnisa, Sherina Rafidah; Puspitasari, Dwi Ajeng; Mahendra, Yusa Okta; Pradastika, Kinanthi Ilham; Budiasih, Budiasih
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1786

Abstract

The results of Basic Health Survey show that the prevalence of adult obesity in Indonesia among people over 18 years of age has doubled from 10.5% in 2007 to 21.8% in 2018. We use data the prevalence of adult obesity as dependent variable and 10 independent variables of socio-economic, food security, and obesity-related risk factors in each regencies/cities in Indonesia. The results showed that there was spatial heterogeneity in prevalence of adult obesity in 514 regencies/cities in 2018. Using Geographically Weighted Regression (GWR), consumption of fatty foods had a positive effect on prevalence of adult obesity in all regions, in contrast to the average length of schooling, consumption of vegetables and soft drinks which only had effect in 501, 448, and 425 regencies/cities. Meanwhile, the poverty percentage, Food Security Index, consumption of instant noodles, and physical activity have a negative effect in 509, 458, 331, and 257 regencies/cities in Indonesia.
Pendugaan Area Kecil Persentase Anak Usia 0-17 Tahun yang Hidup di Bawah Garis Kemiskinan Tingkat Kabupaten/Kota di Pulau Jawa Tahun 2023 Puspitasari, Dwi Ajeng; Herlan, Mumtahanah Ceisa; Fatah, Saifullah; Sedana Nugraha, I Gusti Ngurah Yogi; Manik, Rizky Wahyuda; Istiana, Nofita; Yuniasih, Aisyah Fitri
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.1967

Abstract

Poverty is a problem that continues to confront various countries in the world, with no exception in Indonesia. Poverty reduction is the main focus of the Sustainable Development Goals (SDGs) and the 2020-2024 National Medium-Term Development Plan (RPJMN), with the main focus not only on the poverty of the national population but also the children who live in it. It is known that 47.39 percent, or almost half, of poor children in Indonesia are dominated by Java Island. Therefore, to be able to realize this target, it is necessary to have data availability in small areas, especially areas with a high percentage of poor children on Java Island. This study aims to estimate the percentage of children aged 0-17 years living below the poverty line at the city district level using the Small Area Estimation Hierarchical Bayes (SAE HB) method. Based on the results, estimation using the SAE HB method is able to produce a better Relative Standard Error (RSE) than direct estimation results.
Co-Authors Aisyah Fitri Yuniasih Budiasih Budiasih Fatah, Saifullah Herlan, Mumtahanah Ceisa Istiana, Nofita Khairunnisa, Sherina Rafidah Mahendra, Yusa Okta Manik, Rizky Wahyuda Pradastika, Kinanthi Ilham Prana, Fadhil Aqsa Sedana Nugraha, I Gusti Ngurah Yogi