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The artificial neural network model (ANN) for Malaysian housing market analysis

Abd. Rahman, S. N. and Adi Maimun, N. H. and Mohamed Razali, M. N. and Ismail, S. (2019) The artificial neural network model (ANN) for Malaysian housing market analysis. Page 1 1Student at Universiti Teknologi Malaysia. Email: kikin3005@gmail.com 1 PLANNING MALAYSIA: Journal of the Malaysian Institute of Planners, 17 (1). pp. 1-9. ISSN 1675-6215

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Official URL: https://planningmalaysia.org/index.php/pmj/article...


The Hedonic Model, a traditional method for forecasting house prices has been criticised due to nonlinearity, multicollinearity and heteroskedasticity problems, which were argued to affect estimation accuracy. Unlike the Hedonic Model, the Artificial Neural Network Model (ANN), permits nonlinear relationships and thus avoids the problems plaguing the Hedonic Model resulting in superior forecasting performance. Despite these advantages, attempts to model house prices using ANN are limited in geography and data thus besetting the usefulness of the results. To address the research gap, this paper aims to establish such a new model using ANN in forecasting house prices. A sample of double-storey terraced houses transacted in Johor Bahru are analysed using ANN. The findings illustrate a superior forecasting performance for ANN through high values of goodness of fit and low values of errors. This paper adds to the house price modelling literature and provides new knowledge to both academics and practitioners.

Item Type:Article
Uncontrolled Keywords:artificial neural network model, hedonic model, house price forecasting
Subjects:G Geography. Anthropology. Recreation > G Geography (General) > G70.212-70.215 Geographic information system
Divisions:Geoinformation and Real Estate
ID Code:90939
Deposited By: Narimah Nawil
Deposited On:31 May 2021 21:21
Last Modified:31 May 2021 21:21

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