Bibliographic citations
Ángeles, R., (2023). Inteligencia predictiva, en la prevención del delito de robo, en el distrito de San Juan de Lurigancho, año 2023 [Escuela de Posgrado de la Policía Nacional del Perú]. https://enfpp.repositorio.pnp.edu.pe/handle/123456789/73
Ángeles, R., Inteligencia predictiva, en la prevención del delito de robo, en el distrito de San Juan de Lurigancho, año 2023 []. PE: Escuela de Posgrado de la Policía Nacional del Perú; 2023. https://enfpp.repositorio.pnp.edu.pe/handle/123456789/73
@mastersthesis{sunedu/3694260,
title = "Inteligencia predictiva, en la prevención del delito de robo, en el distrito de San Juan de Lurigancho, año 2023",
author = "Ángeles Puente, Renzo Omar",
publisher = "Escuela de Posgrado de la Policía Nacional del Perú",
year = "2023"
}
The investigation entitled Predictive Intelligence, in the prevention of the crime of robbery, in the district of San Juan de Lurigancho, year 2023, had the objective of determining that predictive intelligence prevents the crime of robbery in the district of San Juan de Lurigancho for the year 2023; A mixed research approach was used with a sequential explanatory design, the population was made up of 1,130 police officers and 2,727 incidents of theft crime in its various modalities that occurred during the year 2021 and the sample was made up of 288 police officers from 8 police stations, 2 DEPINCRIS and 2,727 incidents of the crime of robbery in its various modalities that occurred during the year 2021; Various data collection techniques were used, such as surveys, interviews, and observations, and tools such as questionnaires, interview guides, and observation guides were used. The quantitative results obtained through the three-time model for 2023 indicate that 244 robberies are expected to occur in all forms on January 1. Furthermore, the qualitative results revealed that the majority of respondents believe that the use of predictive intelligence will help prevent theft crimes in 2023. When comparing hypotheses, a high positive correlation was found between predictive intelligence and prevention. Theft, the correlation coefficient was Rho=0.751 (75.1%), and the significance was p=0.000<0.05. In conclusion, it can be determined that predictive intelligence has a significant impact on the reduction of theft incidents in the San Juan de Lurigancho area by the year 2023.
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