📅 23 March 2024
DOI: 10.62951/ijsme.v1i1.13
Using the Geographically Weighted Regression (GWR) Method to Find Out the Factors Causing Poverty in North Sumatra Province
International Journal of Science and Mathematics Education
Asosiasi Riset Ilmu Matematika dan Sains Indonesia (ARIMSI)
📄 Abstract
Poverty is a complex problem that affects various aspects of life in various regions. In this study, we use the Geographically Weighted Regression (GWR) method to identify factors that cause poverty in North Sumatra Province. This approach allows a more detailed analysis of the relationship between independent variables and poverty levels in each geographic location. We use socio-economic and spatial data to build GWR models and identify possible hidden patterns in the distribution of poverty. The findings from this research provide valuable insights for stakeholders to formulate more effective policies in overcoming poverty in North Sumatra Province.
🔖 Keywords
#Poverty; Geographically Weighted Regression (GWR; North Sumatra Province; Factors Causing Poverty; Spatial Analysis
ℹ️ Informasi Publikasi
Tanggal Publikasi
23 March 2024
Volume / Nomor / Tahun
Volume 1, Nomor 1, Tahun 2024
📝 HOW TO CITE
Hilda Pradina Faradiba; aditya syaiful dhuhri, "Using the Geographically Weighted Regression (GWR) Method to Find Out the Factors Causing Poverty in North Sumatra Province," International Journal of Science and Mathematics Education, vol. 1, no. 1, Mar. 2024.
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