Wulandari, Famita Wibi (2026) Analisis Pengaruh Faktor Sosial, Ekonomi, dan Lingkungan Terhadap Produk Domestik Regional Bruto Setiap Provinsi di Indonesia Menggunakan Geographically Weighted Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Produk Domestik Regional Bruto (PDRB) merupakan indikator utama untuk menilai kinerja ekonomi suatu wilayah dan mencerminkan pertumbuhan serta kesejahteraan masyarakat. Di Indonesia, pertumbuhan PDRB masih menunjukkan ketimpangan yang signifikan antarprovinsi, di mana aktivitas dan kontribusi ekonomi cenderung terkonsentrasi pada beberapa wilayah tertentu, sementara wilayah lainnya belum berkembang secara optimal, sehingga pemerataan pembangunan ekonomi belum tercapai. Penelitian ini menggunakan metode Geographically Weighted Regression (GWR) untuk menganalisis pengaruh faktor Sosial, Ekonomi, dan Lingkungan terhadap PDRB di 37 provinsi pada tahun 2024. Metode GWR dipilih karena mampu menangkap variasi spasial dan karakteristik lokal tiap provinsi. Hasil analisis menggunakan metode GWR dengan pembobot Adaptive Bisquare menghasilkan model dengan nilai koefisien determinasi (R²) sebesar 98,93%. Analisis GWR juga menunjukkan bahwa pengaruh faktor Sosial, Ekonomi, dan Lingkungan terhadap PDRB bervariasi di masing-masing provinsi di Indonesia. Hasil penelitian membentuk 9 kelompok provinsi berdasarkan kesamaan pola pengaruh faktor Sosial, Ekonomi, dan Lingkungan terhadap PDRB. Sebagian besar provinsi dalam satu kelompok terletak berdekatan secara geografis, menunjukkan adanya pengaruh lokal terhadap PDRB. Penelitian ini memberikan pemahaman mendalam mengenai distribusi PDRB di Indonesia, sehingga dapat dijadikan dasar bagi pemerintah provinsi dalam merancang kebijakan yang lebih tepat sasaran. Dengan memperhatikan faktor-faktor lokal yang berpengaruh, kebijakan dapat diarahkan untuk mendorong pertumbuhan ekonomi lebih merata, meningkatkan produktivitas tenaga kerja, dan menjaga keberlanjutan pembangunan.
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Gross Regional Domestic Product (GRDP) is a primary indicator for assessing the economic performance of a region and reflects economic growth as well as societal welfare. In Indonesia, GRDP growth still exhibits significant disparities across provinces, where economic activities and contributions tend to be concentrated in certain regions, while others have not developed optimally, resulting in uneven economic development. This study employs the Geographically Weighted Regression (GWR) method to analyze the effects of social, economic, and environmental factors on GRDP across 37 provinces in 2024. The GWR method is chosen because it is capable of capturing spatial variation and local characteristics specific to each province. The results of the GWR analysis using an Adaptive Bisquare weighting function produce a model with a coefficient of determination (R²) of 98.93%. The GWR analysis also reveals that the influences of social, economic, and environmental factors on GRDP vary across provinces in Indonesia. The findings classify provinces into nine groups based on similarities in the patterns of influence of these factors on GRDP. Most provinces within the same group are geographically adjacent, indicating the presence of local effects on GRDP. This study provides a comprehensive understanding of the distribution of GRDP in Indonesia and can serve as a basis for provincial governments in formulating more targeted policies. By considering locally influential factors, policies can be directed toward promoting more equitable economic growth, increasing labor productivity, and ensuring sustainable development.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Ekonomi, GWR, Lingkungan, PDRB, Sosial, Economy, Environment, GRDP, GWR, Social |
| 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: | Famita Wibi Wulandari |
| Date Deposited: | 11 Feb 2026 05:46 |
| Last Modified: | 11 Feb 2026 05:46 |
| URI: | http://repository.its.ac.id/id/eprint/132348 |
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