Multiple Linear Regression on Building Price Prediction with Green Building Determinant

  • Thuraiya Mohd, Syafiqah Jamil and Suraya Masrom

Abstract

Green Building (GB) is known as a potential approach to improve the performance of a building, where in Malaysia it involves five assessment criteria namely; Energy Efficiency (EE), Indoor Environment Quality (EQ), Sustainable Site Planning & Management (SM), Material & Resources (MR), Water Efficiency (WE). All of these criteria will be considered to provide a certification level for GB in Malaysia. To the best of our knowledge, there is still no implementation of the Multiple Linear Regression Analysis (MLR) model on the GB valuation features for building price prediction compared to a conventional building. Besides, spill over the influence of GB has not been found due to limited case studies. This paper attempts to seek the experimental features that may influence the prices of property as well as GB. The empirical experiment was conducted to test the MLR model to study the relationships between the dependent variables (transaction prices) and the independent variables (features). The empirical experiment was based on a Non-GB and GB dataset categorised as Platinum, Gold, Silver, Certified and in Kuala Lumpur District, Malaysia. The results revealed that the Main Floor Area, Green Certificate, Tenure and Number of Bedrooms made statistically significant contributions. Therefore, all of these features contributed and played important roles in the transaction prices.

Published
2020-05-03
How to Cite
Thuraiya Mohd, Syafiqah Jamil and Suraya Masrom. (2020). Multiple Linear Regression on Building Price Prediction with Green Building Determinant. International Journal of Advanced Science and Technology, 29(9s), 1137 - 1148. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13388