Analisis Hubungan Faktor Sosial Ekonomi dan Sebaran Tindak Kriminalitas di Jawa Barat Tahun 2024 dengan Pendekatan Statistika Spasial

Lisma Hermawanti; Dewi Kania Sari

Authors

Lisma Hermawanti Institut Teknologi Nasional Author
Dewi Kania Sari Institut Teknologi Nasional Author

Keywords:

Tindak Kriminalitas, Faktor Sosial Ekonomi, Global Moran's I, LISA

Abstract

West Java Province has a population of more than 50 million people with complex socio-economic dynamics. Factors such as population density, poverty rate, open unemployment, and the Human Development Index (HDI) are suspected to influence the level of crime. According to the National Crime Information Center (2024), there were 43,616 criminal cases in West Java with a crime rate of 86.63 per 100,000 population. This study aims to analyze the relationship between socio-economic factors and crime distribution in West Java in 2024 using a spatial statistics approach, namely Global Moran’s I, Local Indicator of Spatial Association (LISA), and Ordinary Least Squares (OLS) regression. The results show that crime distribution tends to be random, with weak clusters in urban areas. The OLS analysis reveals that among the four independent variables, only HDI has a positive and significant effect on crime, while population density, poverty, and open unemployment are not significant. These findings indicate that higher human development is not always associated with a reduction in crime, particularly in urban areas with intensive socio-economic activities.

References

[1] Badan Pusat Statistik Provinsi Jawa Barat. (2025). Provinsi Jawa Barat dalam Angka 2025. Bandung: BPS Provinsi Jawa Barat.

[2] M. Ilham dan B. H. Wibisono, (2023) “Pola Spasial Kejahatan Pencurian Berdasarkan Aspek Temporal di Kecamatan Kadia,” SPECTA J. Technol., vol. 7, no. 3, pp. 711–722, Dec.

[3] K. S. Pongtiku, T. S. Irja, dan M. R. Riano, (2025) “Analisis Sebaran Tingkat Kriminalitas dan Faktor-Faktor Penyebab di Kota Jayapura,” Kaji. Adm. Publik dan ilmu Komun., vol. 2, no. 2, pp. 327–343.

[4] T. N. S. Sari dan S. Yulianto, (2024) “Analisis Metode Spasial Untuk Menentukan Faktor-Faktor Yang Mempengaruhi Kriminalitas Pada Provinsi Jawa Timur Tahun 2022,” J. Ilm. Din. Sos., vol. 8, no. 2, pp. 289–301.

[5] N. R. Fitriyyah dan S. Pramana, (2024) “Pemodelan Spasial RTH dan Faktor Ekologi Sosial Ekonomi Terhadap Kriminalitas Kota Medan Tahun 2022,” Semin. Nas. Off. Stat., vol. 2024, no. 1, pp. 1097–1108.

[6] P. Burlian, Patologi Sosial, (2016) Jakarta: PT Bumi Aksara: Jakarta: PT Bumi Aksara.

[7] V. Ingilevich and S. Ivanov, (2018) “Crime Rate Prediction In The Urban Environment Using Social Factors,” Procedia Comput. Sci., vol. 136, pp. 472–478.

[8] D. A. Budiartha dan E. D. Anggraini, (2024) “Analisis Pengaruh Indeks Pembangunan Manusia (IPM), Ketimpangan Pendapatan dan Pertumbuhan Ekonomi terhadap Tingkat Kriminalitas di Indonesia,” J. Pendidik. Indones., vol. 5, no. 11, pp. 1203–1216.

[9] S. Septriani, (2024) “The Impact of Economic Conditions on Criminality in Indonesia,” Eur. J. Dev. Stud., vol. 4, no. 3, pp. 68–74.

[10] W. Atthoriq, S. Septriani, dan E. Winarni, (2024) “Analisis Pengaruh Ketimpangan Pendapatan dan Pengangguran Terhadap PDRB Melalui Kriminalitas di Indonesia,” J. Dev., vol. 12, no. 2, pp. 192–209.

[11] Pusat Informasi Kriminal Nasional. (2024). Statistik Kriminal. Diambil kembali dari Pusiknas Bareskrim Polri: https://pusiknas.polri.go.id/

[12] D. A. Yuzani, L. F. Deswina, M. Ifonne, dan Suryadi, (2024) “Pengaruh Faktor Sosial Ekonomi terhadap Tingkat Kriminalitas: Analisis di Kota Tanjungpinang,” SYARIAH J. Ilmu Huk., vol. 1, no. 4, pp. 165–173.

[13] R. Watrianthos, S. Suryadi, Kusmanto, dan S. Samsir, (2023) “Pemetaan Tingkat Kriminalitas di Indonesia: Analisis Spasial dengan Pendekatan SIG pada Tingkat Provinsi,” Bull. Inf. Technol., vol. 4, no. 3, pp. 353–360.

[14] Badan Informasi Geospasial (2024). Geospasial untuk Negeri. Diambil kembali dari Badan Informasi Geospasial: https://tanahair.indonesia.go.id/

[15] J. Law dan A. Y. M. Abdullah, (2025) “Comparisons Between Robbery and Break‐And‐Enter: Area‐Specific Trends, Socioeconomic Risk Factors, and Hotspots Analysis Using a Bayesian Spatial and Spatiotemporal Approach,” Geogr. Anal., vol. 57, no. 3, pp. 463–477.

[16] D. Darnilawati, N. Arifah, H. A.- Bariq, dan S. Kamal, (2018) “Pola Distribusi Kupu-Kupu (Lepidoptera) Di Desa Deudap Pulo Nasi Kecamatan Pulo Aceh Kabupaten Aceh Besar,” Pros. Semin. Nas. Biot. VI 2018, vol. 6, no 1.

[17] D. Desinta, (2022) “Factors Influencing Crime Incidents in West Java Province in 2018-2020,” Media Edukasi Data Ilm. dan Anal. /, vol. 2, no. 1, pp. 1–10.