Green Spaces and Crime: Spatial Modeling of Socio-Economic Influences in Jakarta's Urban Areas, 2022

Abstract

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.

References

Afrianto, F. (2022). East Java province GRDP projection model using night-time light imagery. East Java Economic Journal, 6(2), 208-223.

Al’Alim, M. R., Azizah, M. D. M., & Faristiana, R. A. (2023). Perubahan Sosial Terhadap Lingkungan Masyarakat Dan Perkembangannya: Urbanisasi Dan Teknologi. Tabsyir: Jurnal Dakwah Dan Sosial Humaniora, 4(2), 1–20. https://journal.widyakarya.ac.id/index.php/harmoni-widyakarya/article/view/490%0Ahttps://journal.widyakarya.ac.id/index.php/harmoni-widyakarya/article/download/490/511

Anselin, L., & Li, X. (2020). Tobler’s Law in a Multivariate World. Geographical Analysis, 52(4), 494–510. https://doi.org/10.1111/gean.12237

Bogar, S., & Beyer, K. M. (2016). Green space, violence, and crime: A systematic review. Trauma, Violence, & Abuse, 17(2), 160-171.

BPS. (2023). Statistik Kriminal. Badan Pusat Statistik, 021, 1–62. https://www.bps.go.id/id/publication/2023/12/12/5edba2b0fe5429a0f232c736/statistik-kriminal-2023.html

Branas, C. C., South, E., Kondo, M. C., Hohl, B. C., Bourgois, P., Wiebe, D. J., & MacDonald, J. M. (2011). A citywide cluster randomized trial to restore blighted vacant land and its effects on violence. New England journal of medicine, 365(16), 1509-19.

Brown, C. L. (2018). The built environment and crime: a comparative study of Detroit and Philadelphia. University of Delaware.

Burley, B. A. (2018). Green infrastructure and violence: Do new street trees mitigate violent crime?. Health & place, 54, 43-49.

Nukita, D., & Subiyanto, S. (2017). Kajian Teknis Kontrol Kualitas Tahap Stereokompilasi pada Pembuatan Peta Rupabumi Indonesia Skala 1: 5000 dengan Menggunakan Data Reviewer. Jurnal Geodesi Undip, 6(3), 37-46.

Deng, C. (2015). Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee, Wisconsin. Applied Geography, 65, 38-48.

Farrington, D. P. (2000). Explaining and preventing crime: The globalization of knowledge. Criminology, 38(1), 1–24.

Gascon, M., Sánchez-Benavides, G., Dadvand, P., Martínez, D., Gramunt, N., Gotsens, X., Cirach, M., Vert, C., Molinuevo, J. L., Crous-Bou, M., & Nieuwenhuijsen, M. (2018). Long-term exposure to residential green and blue spaces and anxiety and depression in adults: A cross-sectional study. Environmental Research, 162, 231–239. https://doi.org/10.1016/j.envres.2018.01.012

Haider, M. A., & Iamtrakul, P. (2018). Theoretical concepts of crime and practices in urban planning and design process for safe urban life. International Journal of Building, Urban, Interior and Landscape Technology (BUILT), 12, 7-24.

Jamaludin, A. N. (2017). Sosiologi Perkotaan Memahami Masyarakat Kota dan Problematikanya. Sosiologi Perkotaan, 2(2), 474.

Keputusan Menteri Koordinator Bidang Pembangunan Manusia Dan Kebudayaan Republik Indonesia No.32 Tahun 2022 Tentang Pedoman Umum Pelaksanaan Program Percepatan Penghapusan Kemiskinan Ekstrem, 4 (2022).

Kuo, F. E., & Sullivan, W. C. (2001). Environment and crime in the inner city does vegetation reduce crime? Environment and Behavior, 33(3), 343–367. https://doi.org/10.1177/00139160121973025

KUSMANA, C. (2015). Keanekaragaman hayati (biodiversitas) sebagai elemen kunci ekosistem kota hijau. December 2015. https://doi.org/10.13057/psnmbi/m010801

Meta, Tutorial: Menghitung Indeks Kekayaan Relatif Terbobot Populasi, 2022. https://dataforgood.facebook.com/dfg/docs/tutorial-calculating-population-wei ghted-relative-wealth-index

Mardinsyah, A. A., & Sukartini, N. M. (2020). Ketimpangan ekonomi, kemiskinan dan akses informasi: bagaimana pengaruhnya terhadap kriminalitas di Indonesia. Ekonika: Jurnal Ekonomi Universitas Kadiri, 5(1), 19.

Pringle, D. G. (1984). Urban social geography (Belfast). In Irish geography: the GSI 1934-1984.

Pyle, G. F., Hanten, E. W., Williams, P. G., Pearson, A., & Doyle, J. G. (1974). The spatial dynamics of crime (Vol. 159). Chicago: University of Chicago, Department of Geography.

Rahmawati, S. D., & Apriyanti, D. (2023). Klasifikasi Area Vegetasi dan Non Vegetasi pada Citra Sentinel-2 Menggunakan Metode EVI dengan Google Earth Engine (Studi Kasus: Kabupaten Klaten). Jurnal Ilmiah Geomatika, 3(1), 1. https://doi.org/10.31315/imagi.v3i1.7484

Rivki, M., Bachtiar, A. M., Informatika, T., Teknik, F., & Indonesia, U. K. (2020). PEMETAAN MANGROVE MENGGUNAKAN ALGORITMA MULTIVARIATE RANDOM FOREST. 112.

Riyardi, A., & Guritno, R. B. (2022). Faktor ekonomi yang mempengaruhi penurunan kriminalitas di Provinsi Jawa Tengah: Analisis mikroekonomi. Jurnal Ilmu Kepolisian, 16(1), 12-12.

Sanjaya, S. A., & Fianty, M. I. (2023). Time-based Geospatial Analysis of Night-Time Light Data and Citizen Movement Restriction During Covid-19 Period. G-Tech: Jurnal Teknologi Terapan, 7(2), 664–673. https://doi.org/10.33379/gtech.v7i2.2397

Shepley, M., Sachs, N., Sadatsafavi, H., Fournier, C., & Peditto, K. (2019). The impact of green space on violent crime in urban environments: an evidence synthesis. International journal of environmental research and public health, 16(24), 5119.

Sukartini, N. M., Auwalin, I., & Rumayya, R. (2021). The impact of urban green spaces on the probability of urban crime in Indonesia. Development Studies Research, 8(1), 161–169. https://doi.org/10.1080/21665095.2021.1950019

No, U. U. (26). tahun 2007 tentang tata ruang.(2007).

Uttley, J., Canwell, R., Smith, J., Falconer, S., Mao, Y., & Fotios, S. A. (2024). Does darkness increase the risk of certain types of crime? A registered report protocol. PLoS ONE, 19(1 January), 1–18. https://doi.org/10.1371/journal.pone.0291971

Wang, X., Gerber, M. S., & Brown, D. E. (2012). Extracted from Twitter Posts. 231–238.

Whaites, A. (2016). Achieving the Impossible: Can we be SDG 16 believers? GovNet Background Paper, 2, 1–14. https://search.oecd.org/dac/accountable-effective-institutions/Achieving The Impossible can we be SDG16 believers.pdf

Wicaksono, A. S. (2023). Analisis pengaruh faktor ekonomi terhadap kriminalitas di Kabupaten/Kota Daerah Istimewa Yogyakarta. Jurnal Kebijakan Ekonomi Dan Keuangan, 50-57.

Wizaka, W. (2012). Adaptasi Crime Prevention through Environment Design (CPTED): Studi Kasus Fenomena Desain Fasilitas Publik. ComTech: Computer, Mathematics and Engineering Applications, 3(1), 51. https://doi.org/10.21512/comtech.v3i1.2380