Abstract
The factors that affecting the escalating price of houses in Malaysia are driven by factors such as population growth, income dynamics, interest rates, and GDP. This phenomenon has notably outpaced the growth of household incomes, thus majorly impacting Malaysians. The study’s primary goal is to forecast the housing price index in Malaysia from the best model obtained using Box-Jenkins method. aligning with the 2018-2025 National Housing Policy objectives, utilizing advanced machine learning and time series modeling. The objectives guide the research: to find the best model for predicting house price index in Malaysia using Box-Jenkins Method. Utilizing secondary data from the National Property Information Centre (NAPIC) spanning from 1988 to 2023, the study employed the analytical method of ARIMA. The results favored the ARIMA (1,1,1) model as the best model in predicting housing price indexes. This offers an excellent forecasting model for residential properties towards gaining better understanding of their pricing dynamics and offers potential solutions to the issue of housing affordability for Malaysians.
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