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Using machine learning to forecast residential property prices in overcoming the property overhang issue

Lim, W. Y. and Abu Bakar, N. A. and Hassan, N. H. and Mohd. Zainuddin, N. M. and Mohd. Yusoff, R. C. and Ab. Rahim, N. Z. (2021) Using machine learning to forecast residential property prices in overcoming the property overhang issue. In: 3rd IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2021, 13 September 2021 - 15 September 2021, Kota Kinabalu, Sabah.


Official URL: http://dx.doi.org/10.1109/IICAIET51634.2021.957383...


Overhang property issue has sustained over the past ten years in Malaysia. Major overhang property issue was contributed from the unsold residential property. Though the government announced to build a data system and provide the housing data to prevent a mismatch of supply-demand in the property market, there are still not many relevant studies or research on predicting residential property prices. Hence, it is essential to understand the factors that influence the price of residential properties. The study aims to predict the price of a residential property by using a machine learning algorithm. Three algorithms were selected, namely Decision Tree, Linear Regression, and Random Forest, tested against the training and testing datasets obtained from the Malaysian Valuation and Property Services Department. Results show that the Random Forest model produced high accuracy with lower r_squared (R2), RMSE, and MAE values. Significantly, the study has contributed a new insight into essential property features that primarily influence the property price, which will be useful for property developers and buyers who wish to invest in the property market.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:decision tree, linear regression, machine learning algorithms
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:96030
Deposited By: Narimah Nawil
Deposited On:03 Jul 2022 11:51
Last Modified:03 Jul 2022 11:51

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