TRANSFORMATION OF CRIME COMBAT IN THE DIGITAL ERA: FROM CONVENTIONAL CRIMINAL LAW TO DATA-BASED PREDICTIVE SYSTEMS

Abstract

The development of digital technology has brought significant changes to crime patterns, which are increasingly complex, rapid, and data-driven. This situation demands a transformation in the crime prevention system, which no longer relies solely on conventional, reactive criminal law approaches, but also moves towards data-driven, preventative and predictive approaches. This study aims to analyze the paradigm shift in crime prevention from conventional models to data-driven predictive systems from a criminal law perspective. The research method used is normative juridical with a statutory and conceptual approach. The results show that the conventional criminal law system has limitations in responding to the dynamic nature of digital crime, so the integration of technologies such as big data and artificial intelligence is necessary to support early detection and crime prevention. However, the implementation of predictive systems must still adhere to the principles of legality, legal certainty, and protection of human rights to avoid abuse of authority and algorithmic bias. Thus, the transformation of crime prevention in the digital era is an urgent need to create a criminal justice system that is more effective, adaptive, and responsive to technological developments.