The Relationship between Socioeconomic Factors and Crime at the Provincial Level in Indonesia: A Linear Regression Approach

Authors

  • Herdin Kristianjani Zebua Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia Author
  • Muhamad Fikri Zaelani Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia Author
  • Rifqi Lutdan Padl Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia Author
  • Irsyad Nur Hidayatulloh Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia Author
  • Mahesa Adlan Falah Department of Informatics, UIN Sunan Gunung Djati Bandung, Indonesia Author

Keywords:

crime rate, socioeconomic factors, linear regression, correlation analysis, unemployment rate,, prediction, indonesia

Abstract

Background: Crime is a complex social phenomenon that is closely associated with socio-economic conditions. Understanding the relationship between economic factors and crime is important for developing evidence-based policies, particularly in the context of regional disparities in Indonesia.

Purpose: This study aims to examine the relationship between socio-economic factors and crime rates at the provincial level in Indonesia and to assess the extent to which these factors can explain variations in crime.

Methods: This study uses secondary data at the provincial level in Indonesia. The analysis was conducted using descriptive statistics, correlation analysis, data visualization, and multiple linear regression. The variables analyzed include crime rate, population, unemployment rate, poverty level, and education level.

Results: The results indicate a significant positive relationship between crime rates, population, and unemployment rate, which is consistent with the economic perspective on crime. In contrast, poverty and education show weak or inconsistent relationships with crime, suggesting a more complex interaction. The multiple linear regression model yields very limited explanatory power, with an R-squared (R²) value of 0.03, indicating that the selected socio-economic variables explain only a small share of the variation in crime rates.

Conclusions: The findings suggest that crime cannot be sufficiently explained by the selected socio-economic indicators alone. Other factors, such as social cohesion, inequality, urban social conditions, and the effectiveness of law enforcement, may play a substantial role in shaping crime patterns. Therefore, a more comprehensive analytical approach and richer data are needed to support more effective crime prevention policies.

Research Contribution: This study contributes to the literature by showing the limited explanatory capacity of macro-level socio-economic variables in explaining crime rates in Indonesia and by highlighting the importance of incorporating broader social and institutional factors in future research.

References

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Published

2026-04-05

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Vol. 1 No. 1 (2026)

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