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@article{J.Gauss46622, author = {Nurul Ulya Ayudia and Dina Eka Putri}, title = {PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR}, journal = {Jurnal Gaussian}, volume = {13}, number = {2}, year = {2024}, keywords = {Spatial regression; spatial autogressive model (SAR); poverty}, abstract = {Poverty is a trigger for one of the serious issues in the development process in Indonesia. Various measures have been undertaken by countries around the world to eradicate poverty, and this eradication agenda is listed in the first goal of the Sustainable Development Goals (SDGs), which is \"No Poverty,\" with the target that all countries in the world will strive to eliminate all forms of poverty by 2030. This study aims to conduct an analysis model regarding the Spatial Autoregressive Model (SAR) to demonstrate the spatial effects of the relationship between independent variables and the dependent variable, with a case study of Poverty in Regencies/Cities in East Java in 2023. Factors that have a significant influence on poverty include the Gini Ratio (X1), average years of schooling (X2), per capita expenditure (X3), and the percentage of households receiving PKH (X7). The model shows that the variability in poverty can be explained by this model by 80.10%, indicating that the model has a good fit, while 19.9% is explained by other variables outside the model.}, issn = {2339-2541}, pages = {308--318} doi = {10.14710/j.gauss.13.2.308-318}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/46622} }
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