Application of the Autoregressive Integrated Moving Average (ARIMA) Method in Forecasting the Number of Young Construction to Support Human Resource Planning in the Construction Sector - Nadeak, Vincentius Danu Bona Arta; Limbong, Daniel Isar Valentino; Sirait, Glenn Desmon; Sitorus, Johannes Antonius Kristian; Hardinata, Jaya Tata (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2026)
This study aims to apply the ARIMA method in predicting the number of young construction workers in Indonesia during the period 2012 to 2022. The data source used is from the Badan Pusat Statistik(BPS), which includes data on skilled workers in 34 provinces in Indonesia. In this study, three different ARIMA models were tested, namely ARIMA(1,1,1), ARIMA(0,1,1), and ARIMA(1,1,0), to see which model provided the best prediction results. Based on the evaluation results using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE), the ARIMA(0,1,1) model showed the best performance with the smallest MSE and the lowest MAPE, which was 2.5%. These results indicate that simpler ARIMA models, such as ARIMA(0,1,1), are more effective in predicting the demand for young construction workers, thereby assisting in more targeted training planning, resource distribution, and development policies. This study is expected to make a significant contribution to the development of the construction sector in Indonesia by providing a solid basis for data-driven decision-making in workforce planning in this sector.