Putri, Clarissa Rexana (2025) Pemodelan Faktor-Faktor Yang Memengaruhi Prevalensi Balita Underweight Di Provinsi Jawa Tengah Dengan Metode Geographically Temporally Weighted Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Underweight adalah kondisi saat berat badan pada anak berada dibawah rentang rata-rata atau normal. Salah satu provinsi penyumbang kasus balita underweight terbanyak di Pulau Jawa adalah Provinsi Jawa Tengah. Berdasarkan data Dinas Kesehatan Jawa Tengah, prevalensi balita underweight di provinsi ini mengalami peningkatan berturut-turut dari 6,2% pada tahun 2021, kemudian 8,6% pada tahun 2022, dan naik menjadi 10,56% pada tahun 2023. Tren peningkatan ini menunjukkan bahwa diperlukan faktor-faktor yang dapat dikatakan turut berkontribusi dalam upaya menurunkan prevalensi balita underweight. Penelitian ini menggunakan metode Geographically Weighted Regression (GWR) dan Geographically Temporally Weighted Regression (GTWR) dengan fungsi Fixed Gaussian Kernel. Penelitian ini bertujuan untuk menganalisis karakteristik dan mendapatkan faktor-faktor penyebab prevalensi balita underweight di Provinsi Jawa Tengah pada tahun 2023. Pemodelan menggunakan GWR menghasilkan R² sebesar 0,82. Pemodelan GTWR tahun 2022–2023 memberikan performa terbaik menghasilkan R² tertinggi dan AIC terendah dibandingkan dengan pemodelan GTWR tahun 2021–2023. Hasil GWR dan GTWR menunjukkan bahwa variabel signifikan membentuk dua dan delapan kelompok berdasarkan kesamaan variabel signifikansi dan arah pengaruh variabel tanda estimasi koefisien regresi. Variabel yang berpengaruh signifikan di seluruh kabupaten/kota yaitu prevalensi balita pendek pada GWR, sedangkan variabel persentase bayi baru lahir mendapat IMD berpengaruh signifikan dibeberapa kabupaten/kota. Pada GTWR juga memiliki variabel persentase bayi BBLR, sanitasi layak, bayi baru lahir mendapat IMD, diare pada balita, dan balita pendek yang berpengaruh signifikan hanya dibeberapa kabupaten/kota tertentu.
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Underweight refers to a condition in which a child's weight falls below the normal or average range. One of the provinces with the highest number of underweight children in Java Island is Central Java Province. According to data from the Central Java Health Office, the prevalence of underweight children in this province has shown a continuous increase: from 6.2% in 2021, to 8.6% in 2022, and rising to 10.56% in 2023. This upward trend indicates the need to identify contributing factors that influence efforts to reduce underweight prevalence. This study applies the Geographically Weighted Regression (GWR) and Geographically Temporally Weighted Regression (GTWR) methods using a Fixed Gaussian Kernel function. The aim is to analyze characteristics and identify the factors influencing the prevalence of underweight children in Central Java Province in 2023. The GWR model produced an R² value of 0.82. The GTWR model using data from 2022–2023 showed the best performance, achieving the highest R² and the lowest AIC compared to the GTWR model using 2021–2023 data. The GWR and GTWR results indicate that the significant variables form two and eight groups, respectively, based on similar significant variables and the direction of the regression coefficient estimates. The prevalence of stunting among children was found to be a significant factor across all districts/cities in the GWR model. Meanwhile, in some districts/cities, the percentage of newborns receiving early initiation of breastfeeding (IMD) was also significant. In the GTWR model, several variables showed significant effects in certain regions only, including the percentage of low birth weight (LBW) infants, access to proper sanitation, newborns receiving IMD, diarrhea cases among children, and stunting in children.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Gaussian, GTWR, GWR, Jawa Tengah, Underweight, Central Java, Gaussian, GTWR, GWR, Underweight |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression Q Science > QA Mathematics > QA353.K47 Kernel functions (analysis) R Medicine > RJ Pediatrics > RJ101 Child Health. Child health services |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Clarissa Rexana Putri |
| Date Deposited: | 01 Aug 2025 01:40 |
| Last Modified: | 01 Aug 2025 01:40 |
| URI: | http://repository.its.ac.id/id/eprint/125020 |
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