Geographic Information System Mapping Risk Factors Stunting Using Methods Geographically Weighted Regression - Rambe, Siska Mayasari; Suendri, Suendri (Journal of Applied Geospatial Information, 2023)
Technological developments in this era of globalization are very rapid. This requires humans to enter life together with information and technology. Stunting as a chronic nutritional problem in children, continues to be a global challenge. Geographic Information Systems (GIS) have proven to be effective tools in spatial analysis and distribution mapping stunting. In this context, method Geographically Weighted Regression (GWR) has been used to model the spatial relationship between factors that contribute to stunting. This research will produce a Geographic Information System using the method Geographically Weighted Regression. With this Geographic Information System, it can display location points and affected information stunting. Because of this system, the Padang Lawas Utara District Health Office does not need to store location data stunting in archive form again but digitally. This study underscores the importance of using GIS with the GWR method in mapping patient locations stunting. Through the integration of geographic data and spatial analysis, we can generate a better understanding of the influencing factors stunting at the local level, which in turn can support prevention and response efforts stunting which is more effective.