Pengembangan WebGIS Untuk Analisis Dan Pemodelan Data Menggunakan Teknik Regresi Spasial Dan R-Shiny Web Framework (Studi Kasus: Data Kemiskinan dan Zakat Jawa Timur)

Gibranda Gibranda (Fakultas Ilmu Komputer, Universitas Brawijaya)
Fatwa Ramdani (Fakultas Ilmu Komputer, Universitas Brawijaya)
Ismiarta Aknuranda (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 3 (2018): Maret 2018

Regression analysis is a common method used to see the relationship between dependent and independent variable. Regression analysis has global properties and is applied to all sites observed. However, the condition of poverty and zakat in the districts / cities in the Province of East Java certainly has different characteristics, based on its geographic conditions, potential areas, socio-cultural circumstances and other things behind it, resulting spatial heterogeneity. Geographically Weighted Regression (GWR) is the solution to create local regression. Shiny Web Framework from R software able to perform spatial regression analysis. R is an open-source tool Statistics that can be used to perform spatial regression data analysis and modeling. Shiny is a web-based framework for building web-based applications. This research builds a web-based application to perform spatial regression analysis and modeling with Shiny Web Framework. The data used in this research is zakat data and poverty of east java province. The results of this study produce WebGIS tool with 10 functional. While the result of spatial regression analysis using GWR method gives R-square value of 76%.