Rising Cost Forecasting Model for Selected Material Used in Construction Industry

Abstract: The construction industry is vital for economic growth, but fluctuating material prices pose challenges, especially in times of crisis. Uncertainty leads to losses for contractors, affecting countless people and projects. This paper aims to understand the correlation between economic conditions and material prices, developing models to forecast future costs. Utilizing time series and artificial neural networks, a study in Malaysia found that the ANN model outperforms traditional methods, with lower prediction errors. Continuous review and model refinement are crucial for accuracy. This research aids in budgeting and identifying factors influencing construction costs, assisting clients and contractors in navigating price fluctuations effectively. Keywords: Time Series, Neural Network, Forecasting JEL Classification Number: F31, F41