<![CDATA[Traffic congestion in Indonesia causes significant economic losses and impacts the quality of life of the community. The Smart Traffic Management System (STMS) emerges as a technology-based solution that integrates the Internet of Things (IoT), Artificial Intelligence (AI), and big data to manage vehicle flow adaptively. This research employs the Systematic Literature Review (SLR) method with the PRISMA approach to analyze the effectiveness of STMS in reducing congestion and carbon emissions, both in Indonesia and in other countries. The reviewed articles indicate that STMS can reduce vehicle travel time by 8-15%, improve traffic flow smoothness by up to 50%, and decrease carbon emissions by 30-40% per year. Trials in Jakarta demonstrate a 15% increase in traffic smoothness and a reduction in travel time during peak hours. These findings confirm that the implementation of STMS has tremendous potential to realize a more efficient, safe, environmentally friendly, and sustainable urban transportation system.]]>
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