1# RECORD 321664826269788c8435ead0315a2539fb9837f32# TITLE: ENHANCING THE ACCURACY OF MALAYSIAN HOUSE PRICE FORECASTING: A COMPARATIVE ANALYSIS ON THE FORECASTING PERFORMANCE BETWEEN THE HEDONIC PRICE MODEL AND ARTIFICIAL NEURAL NETWORK MODEL3# YEAR: 2021.0 VENUE: PLANNING MALAYSIA DOI: 10.21837/pm.v19i17.10034# AUTHORS: Nurul Fazira Sa’at; N. H. Adi Maimun; N. H. Idris5# PAGES: 11 CANDIDATE TABLE PAGES (1-based): []6# ABSTRACT: The Hedonic Price Model (HPM), a prominent model used in real estate appraisal and economics, has been argued to be marred with nonlinearity, multicollinearity and heteroscedasticity problems that affect the accuracy of price predictions. An alternative method called Artificial Neural Network Model (ANN) was identified as capable of addressing the shortcomings of HPM and produces superior predictive performance. Hence, this study aims to evaluate the forecasting performance between HPM and ANN using Malaysian housing transaction data from the period between 2009 to 2018, sourced from the Valuation and Property Service Department, Johor Bahru. The models’ performance was evaluated and compared based on their statistical and predictive performance. Results showed that ANN outperformed HPM in both statistical and predictive performance. This study benefits the expansion of academic and practical knowledge in enhancing the accuracy of house price forecasting.789===== PAGE 1 (score 1, numeric-paren 0, table-words 0, var-words 1) =====1011 12 13 141 Research Assistant at Universiti Teknologi Malaysia. Email: nurulfazirasaat@gmail.com 15PLANNING MALAYSIA: 16Journal of the Malaysian Institute of Planners 17VOLUME 19 ISSUE 3 (2021), Page 249 – 259 18ENHANCING THE ACCURACY OF MALAYSIAN HOUSE PRICE 19FORECASTING: A COMPARATIVE ANALYSIS ON THE 20FORECASTING PERFORMANCE BETWEEN THE HEDONIC PRICE 21MODEL AND ARTIFICIAL NEURAL NETWORK MODEL 22 23Nurul Fazira Sa’at1, Nurul Hana Adi Maimun2 & Nurul Hazrina Idris3 24 251,2Centre for Real Estate Studies, Institute for Smart Infrastructure and 26Innovative Construction, 27UNIVERSITI TEKNOLOGI MALAYSIA 283Geoscience and Digital Earth Centre, Research Institute for Sustainable 29Environment (RISE), 30UNIVERSITI TEKNOLOGI MALAYSIA 31 32 33Abstract 34 35The Hedonic Price Model (HPM), a prominent model used in real estate appraisal 36and economics, has been argued to be marred with nonlinearity, multicollinearity 37and heteroscedasticity problems that affect the accuracy of price predictions. An 38alternative method called Artificial Neural Network Model (ANN) was identified 39as capable of addressing the shortcomings of HPM and produces superior 40predictive performance. Hence, this study aims to evaluate the forecasting 41performance between HPM and ANN using Malaysian housing transaction data 42from the period between 2009 to 2018, sourced from the Valuation and Property 43Service Department, Johor Bahru. The models’ performance was evaluated and 44compared based on their statistical and predictive performance. Results showed 45that ANN outperformed HPM in both statistical and predictive performance. This 46study benefits the expansion of academic and practical knowledge in enhancing 47the accuracy of house price forecasting. 48 49 50Keywords: Property forecasting, property valuation, predictive accuracy, hedonic 51price model, artificial neural network 52 53