Geoadditive Semiparametric Regression For Modeling Property Price In Surabaya, Indonesia Using Marketplace Data

Abstract

The price growth of the property in Surabaya is the highest among the other cities in East Java, but demand in the residential sub-sector is still there. The value of a property is described by its price. Property price is one of the important factors considered in making an investment decision. The market value is determined by its physical and micro-neighborhood factors. It consists of location and environmental factors. Mass appraisal is an efficient and cost-effective way to value property fairly, transparently, and consistently, as properties with the same attributes will receive equal value. The existence of a price property model is vital in the context of mass appraisal. The objective of mass appraisal is to value a group of properties using data, valuation methods, and statistical tests. Mass appraisal is invaluable for the government to formulate taxes based on the market value. In this research, the Geoaditive model is used to model property price based on its physical and location factors. The results show that the physical (number of bedrooms, number of bathrooms, land area, and building area) and location (longitude and latitude coordinates) factors significantly influence the property prices in Surabaya. The building area has more impact on the property price compared to the land area. The combined effect plot shows also that the properties located in the eastern of Surabaya have a relatively higher price than those in the western part