Prediction of Carbon Emissions in Indonesia Using Machine Learning: A Focus on Environmental Impact

Putra, Rizaldi
Sanjaya, Memet
Utama, Deni
Berliana, Berliana

JISA (Jurnal Informatika dan Sains)
Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains)

Carbon emissions represent a critical driver of global climate change, exerting profound impacts on environmental sustainability and public health. This research examines Indonesia's carbon emission trends using a comprehensive dataset spanning global emissions from 1960 to 2018, with specific focus on Indonesia, obtained from Kaggle. Employing Linear Regression (LR) as the primary machine learning technique, the study effectively models and forecasts future carbon emission levels for Indonesia. The findings indicate a projected increase in emissions to 2.38 tons per capita annually by 2030, underscoring the urgent need for robust environmental policies.