HOW DATA MINING CAN BE USED TO IDENTIFY SPECIFIC CRIME PATTERNS IN THE CITY OF NATAL/RNBASED ON THE CHICAGO SCHOOL THEORY OF CRIMINOLOGY
Keywords:
Criminalidade, Segurança Pública, Técnicas Avançadas, Mineração de Dados, Algoritmos de Machine Learning, CRISP-DM, Padrões, Perfis, Cidade do Natal RNAbstract
Year after year, the increasing volume of data on crime in the state of Rio Grande do Norte (RN) exposes the fragility of the public security system and the new challenges. This prompts the use of advanced techniques to seek and extract valuable insights for the public security sector. This article proposes a modern perspective that combines data mining and machine learning algorithms with the CRISP-DM methodology. This arrangement aims to identify patterns and profiles of various crimes in Natal City, RN, enhancing the understanding of their occurrences by region and neighborhood within the city. The numbers indicate that this approach is not only effective as a tool for optimizing strategies but also has the ability to identify specific behavioral patterns. In the pursuit of crime prevention and reduction, this focus points to an effective remedy for addressing disputes related to criminality in RN.
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Copyright (c) 2025 Stefani Leite Cavalcanti, Wagner Márcio Marques Cabral, Horácio Betcel Guimarães, Orivaldo Vieira de Santana Júnior, Efrain Pantaléon Matamoros
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
