Promoting evidence-based energy transition: Utilizing statistical analysis for energy and sustainability policies in Indonesia

Abstract

Indonesia’s energy transition faces increasing urgency as fossil fuels continue to dominate the national energy supply and contribute significantly to carbon emissions. This paper employs three statistical approaches, including ARIMA forecasting, multiple regression, and Monte Carlo simulation, to evaluate future energy trends and the feasibility of achieving national renewable energy targets. ARIMA results indicate that coal and oil remain the main contributors to the energy mix until 2060, while renewable energy grows slowly and remains below policy targets. Multiple regression confirms that fossil energy consumption has a significant and positive effect on CO₂ emissions, whereas renewable energy shows an insignificant contribution to emission reductions. Monte Carlo simulations further reveal a bifurcated reality: the probability of achieving the 23% renewable energy target by 2025 is relatively high, at 65.21%, due to recent bioenergy policy momentum, while the likelihood of meeting the 2060 target of 78% is 0.00% under current projected trends. These findings highlight that while short-term goals are within reach, a profound structural gap remains in achieving long-term decarbonization. This finding emphasizes the urgent need for targeted policy interventions, specifically combining short-term bioenergy optimization with an aggressive, mandated phase-down of coal dependency and accelerated investment in renewable technologies. A more adaptive, data-driven policy framework is essential for enhancing Indonesia’s transition toward sustainable and low-emission energy systems.