<![CDATA[Urban crime is a multidimensional issue influenced by environmental, economic, and social interactions. This study investigates factors affecting crime rates in DKI Jakarta, including green open space (RTH), night light intensity (NTL), security services and worship facilities, extreme poverty, relative wealth index (RWI), and population density. Using remote sensing and spectral indices, green open spaces were identified and classified with a random forest model, achieving 95.53% overall accuracy and a kappa coefficient of 94.19%. Spatial regression analysis with Queen Contiguity weights was employed to examine the influence of these factors on crime rates. Results from the Spatial Autoregressive Moving Average (SARMA) model show that green space area, NTL, and extreme poverty significantly impact crime rates. Districts with more green spaces, such as South Jakarta, experienced lower crime rates, while densely populated and impoverished areas, such as North Jakarta, exhibited higher crime rates. The study highlights the importance of ecological factors in crime prevention, emphasizing the integration of green space planning and big data analytics. These findings provide actionable insights for policymakers to develop safer urban environments and support Indonesia’s efforts toward achieving SDG 16 on peace and justice.]]>
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