<![CDATA[This study aims to apply the Autoregressive Integrated Moving Average (ARIMA) model to predict national economic growth, specifically focusing on Gross Domestic Product (GDP) data. GDP data were collected from 2012 to 2023, categorized into training data for the period 2012-2022 and testing data for the year 2023. Utilizing the training data, the research findings indicate that the ARIMA (0,1,0) (0,0,1) model emerges as the most effective in forecasting Indonesia's GDP on a quarterly basis, considering current prices. Subsequently, the model was tested on the 2023 dataset, and it demonstrated accurate predictions aligned with patterns and trends identified during the training phase. The outcomes of this research contribute significantly to the field of economic forecasting in Indonesia, particularly in understanding and predicting the quarterly developments of GDP. The proposed ARIMA model can serve as an effective tool for decision-makers and economic analysts to strategically plan for future economic dynamics on a quarterly basis.]]>
Copyrights © 2024
