Toward Indonesia Cement Decarbonization: A Survey on Machine Learning Model

Climate change and global warming present significant global challenges, urging industries to embrace sustainable practices. In Indonesia, the cement industry is a major contributor to greenhouse gas (GHG) emissions, accounting for 4% of global CO2 emissions. This paper outlines a decarbonization roadmap for Indonesia's cement sector, targeting net-zero emissions (NZE) by 2050. Key approaches include lowering the clinker factor, using alternative fuels, improving energy efficiency, and implementing advanced technologies such as Carbon Capture and Storage (CCS). An ensemble learning model is introduced to forecast GHG emission reduction scenarios and optimize mitigation strategies. By harnessing artificial intelligence, the model provides precise predictions and actionable recommendations to effectively curb emissions. The research highlights Indonesia’s dedication to global climate commitments, emphasizing the cement industry's vital role in achieving the country’s Enhanced Nationally Determined Contribution (ENDC) goals. This ongoing study establishes a framework for integrating cutting-edge machine learning techniques into decarbonization initiatives, supporting sustainable development in Indonesia's cement industry.