PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR

Nurul Ulya Ayudia; Dina Eka Putri

doi:10.14710/j.gauss.13.2.308-318

DOI: https://doi.org/10.14710/j.gauss.13.2.308-318

PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR

Nurul Ulya Ayudia - Department of Mathematic, Universitas Mataram, Jl. Majapahit No. 62, Gomong, Kec. Selaparang, Kota Mataram, Nusa Tenggara Barat, Indonesia

*Dina Eka Putri - Department of Statistic, Universitas Mataram, Jl. Majapahit No. 62, Gomong, Kec. Selaparang, Kota Mataram, Nusa Tenggara Barat, Indonesia

How to cite (IEEE): N. U. Ayudia, and D. E. Putri, "PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR," Jurnal Gaussian, vol. 13, no. 2, pp. 308-318, Nov. 2024. https://doi.org/10.14710/j.gauss.13.2.308-318

How to cite (APA): Ayudia, N. U., & Putri, D. E. (2024). PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR. Jurnal Gaussian, 13(2), 308-318. https://doi.org/10.14710/j.gauss.13.2.308-318

How to cite (BCREC): Ayudia, N. U., Putri, D. E. (2024). PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR. Jurnal Gaussian, 13 (2), 308-318 (doi:10.14710/j.gauss.13.2.308-318)

How to cite (Chicago): Ayudia, Nurul U., and Dina E. Putri. "PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR." Jurnal Gaussian 13, no. 2 (2024): 308-318. Accessed : April 3, 2025. https://doi.org/10.14710/j.gauss.13.2.308-318

How to cite (Vancouver): Ayudia NU, Putri DE. PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR. Jurnal Gaussian [Online]. 2024 Nov;13(2):308-318. https://doi.org/10.14710/j.gauss.13.2.308-318.

How to cite (Harvard): Ayudia, N. U., and Putri, D. E., 2024. PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR. Jurnal Gaussian, [Online] Volume 13(2), pp. 308-318. https://doi.org/10.14710/j.gauss.13.2.308-318 [Accessed : 3 Apr. 2025].

How to cite (MLA8): Ayudia, Nurul Ulya, and Dina Eka Putri. "PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR." Jurnal Gaussian, vol. 13, no. 2, 11 Nov. 2024, pp. 308-318 , https://doi.org/10.14710/j.gauss.13.2.308-318. Retrieved : 3 Apr. 2025.

BibTex Citation Data :

@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}
}

Refworks Citation Data :

@article{{J.Gauss}{46622}, author = {Ayudia, N., Putri, D.}, title = {PEMODELAN SPATIAL AUTOREGRESSIVE MODEL (SAR) PADA KASUS KEMISKINAN DI JAWA TIMUR}, journal = {Jurnal Gaussian}, volume = {13}, number = {2}, year = {2024}, doi = {10.14710/j.gauss.13.2.308-318}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/46622} }

Citation Format:

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.

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Keywords: Spatial regression; spatial autogressive model (SAR); poverty

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In Vol 13, No 2 (2024): Jurnal Gaussian