Strengthening Predictive Policing Approaches to Improve Urban Safety Outcomes - Lesha Syabrina (Universitas Negeri Semarang, 2025)
This study analyzes the effectiveness of predictive policing technologies in enhancing urban security, particularly in rapidly growing metropolitan areas. As cities expand, law-enforcement institutions face increasingly complex challenges related to crime patterns, mobility, and social dynamics. The primary objective of this research is to evaluate how data-driven crime prediction models, integrated with digital surveillance and community reporting systems, influence overall police performance and public safety outcomes. A mixed-methods approach was employed, combining statistical crime-trend analysis (2016–2023) with interviews involving police analysts, patrol officers, and urban residents. Results indicate that predictive policing systems contributed to a 22% reduction in hotspot-related crime and improved the accuracy of patrol deployment. Interview findings show improved officer confidence in decision-making and increased public trust due to transparent risk-mapping practices. The study concludes that predictive policing can significantly strengthen urban safety strategies if implemented ethically and inclusively. This research contributes to the growing body of knowledge on technology-supported policing and offers policy insights for sustainable security development.