Abstract
Geographically Weighted Logistic Regression (GWLR) is a local form of logistic regression where geographical factors considered and it is assumed that the Bernoulli distribution of data used to analyze spatial data from non-stationary processes. This research will determine the factors that affect the Population Growth Rate (PGR) in the Semarang city using logistic regression and GWLR with a weighting function of bisquare kernel and gaussian kernel. The result showed that GWLR model with a weighting function of bisquare kernel better than logistic regression model and GWLR model with a weighting function of gaussian kernel because it has the smallest AIC value and classification accuracy is 87,5%. Factor that have significant effect is the number of couples of childbearing age in the Semarang city.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
