Land value capture modeling in commercial and office areas using a big data approach

Abstract

Infrastructure development in Indonesia creates massive impacts on the economy. The Light rail transit (LRT) of greater Jakarta (Jabodebek) project has been estimated to have cost more than 29 trillion rupiahs due to land acquisition and route planning. The urban transit development may impact to the price of property including residential, commercials and offices along the route. This research aims to determine variables affecting the price elasticity of property and the correlation to station proximity. Data mining through web scrapping was used to assess the degree of correlation between price elasticity and station location. The result shows that approximately 13% of the commercial property was spread over a distance of 1 km from the LRT station. The closer a property to transit station, the price will be twice cheaper compared to those located further. The findings also show variables that highly contribute to property prices including schools, hospitals, and proximity to some of transit stations located in city center of Jakarta and building density.