Forecasting Indonesia’s Final Energy Consumption Using ARIMA Models: Evidence from 2001–2024 and Projections to 2030

Abstract

Reliable projections of energy consumption are essential for designing effective and sustainable energy policies in emerging economies such as Indonesia, where demand continues to rise alongside economic growth and population expansion. This study forecasts Indonesia’s final energy consumption using the Autoregressive Integrated Moving Average (ARIMA) approach, with historical annual data covering 2001–2024 and projections extending to 2030. Accurate forecasting is essential for Indonesia because rising economic activity, urbanization, industrial expansion, population growth, and increasing household energy demand continue to place pressure on national energy security and sustainability. The study applies the Box–Jenkins procedure through stationarity testing, model identification, parameter estimation, diagnostic checking, and out-of-sample forecasting using EViews. The Augmented Dickey–Fuller test indicates that the original series is non-stationary at level, but becomes stationary after first differencing. Model comparison based on the Akaike Information Criterion, Schwarz Criterion, R-squared value, residual correlogram, and diagnostic probability values identifies ARIMA (1,1,1) as the most appropriate specification for forecasting Indonesia’s final energy consumption. The empirical results show a persistent upward trend, with final energy consumption increasing from 3,807,815 TJ in 2001 to 7,930,428 TJ in 2024. Forecasts suggest that consumption will continue to rise from 7,948,819 TJ in 2025 to 8,926,521 TJ in 2030. These findings indicate that Indonesia will face growing pressure to secure reliable, affordable, and sustainable energy supplies. The study contributes to energy policy planning by providing quantitative evidence for strengthening energy infrastructure, improving energy efficiency, accelerating renewable energy adoption, and reducing dependence on fossil fuels. The results also highlight the importance of integrating demand forecasting into long-term national energy strategies to support sustainable development and energy resilience.