Regional Clustering of CO₂ Emissions in Indonesia for Emission Policy Targeting
Abstract
Regional disparities in Indonesia’s CO2 emissions highlight the need for emissions policies tailored to regional conditions rather than uniform national policies. This study addresses this issue by applying clustering analysis to identify emission patterns across five sectors: Energy, IPPU, Agriculture, Forestry, and Waste. K-Medoids and Fuzzy K-Medoids were selected for their robustness to outliers and their ability to capture complex, cross-sectoral emission characteristics more effectively than conventional methods. The results show that the K-Medoids method produced the most reliable clustering, with a Silhouette Coefficient of 0.5981 and a Dunn Index of 0.0310, indicating a moderate cluster structure. Two clusters were identified: provinces with low emissions dominated by the forestry sector, and provinces with high emissions driven by non-forestry activities. These cluster-based patterns provide a practical basis for directing emission policy interventions according to regional characteristics.
Keywords
References
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DOI: http://dx.doi.org/10.30829/zero.v9i2.26449
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