#TITLE_ALTERNATIVE#

• Main Author: Amanda Utari, Nadya
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/29498
• Institution: Institut Teknologi Bandung

<p align="justify">Land price can be influenced by many factors, including the vicinity to the facilities needed such as road, central business, etc. Information of land price is required by many parties for various purposes, such as investment, or to set a reasonable average land price of an area, commonly called Nilai Objek Jual Objek Pajak (NJOP). One method for assessing land prices is regression that models relationship between land prices and the variables that contribute to the value of land price. Modeling the land price needs to be done continuously especially in developing areas such as District Gedebage. <br /> <br /> <br /> <br /> This final project aimed to model the land price using the Geographically Weighted Regression (GWR), which is a regression method that takes into account spatial variations by applying geographic weight to the model. Rather than global model, GWR method generates model with local coefficient of parameters. In this final project, compared to the multiple linear regression result as the global regression model with R2 value of 0.21, the result of GWR showed a better land pricing model with R2 value of 0.37.<p align="justify"> <br />