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Influence of Intelligence Data Utilization in Crime Prevention in Nairobi City County, Kenya

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Many jurisdictions across the globe are increasingly implementing intelligence management as a strategy for crime prevention. The study thus sought to determine the degree to which intelligence data utilization facilitates crime prevention in Nairobi City County. The Routine Activities Theory served as a guide for the investigation. The study population consisted of 556 criminal investigations officers (CIOs) from all Nairobi County sub-counties as well as sub-county criminal investigations heads, and a descriptive survey research technique was used. The study used the Yamane formula to calculate a sample size of 247 criminal investigations officers and conducted a census of all CIO sub-county heads. In order to calculate the number of officers in each sub-county whereby, stratified random sampling was utilized. Officers chosen for the study were given semi-structured questionnaires, and data was gathered through personal interviews with CIO sub-county heads. The Kiambu sub-county police division served as the site of the pilot research. The data was analyzed using the Statistical Package for Social Sciences (SPSS). The correlation analysis results revealed that there was a positive and a strong significant association between intelligence data utilization and crime prevention (r=0.669, p=0.000<0.05). The hypothesis test results show that intelligence data utilization influences crime prevention (β = 0.619, ρ = 0.000< 0.05). The study concludes that intelligence data utilization significantly and powerfully affects crime prevention in Nairobi City County. However, Nairobi City County's current use of intelligence data for crime prevention is severely hampered by a number of significant factors. Officers are unable to map offenders and crime scenes using predictive data or do effective crime diagnostics because they lack the necessary training in interpreting intelligence data. The study recommends that the National Government's Ministry of Interior & Coordination adopt and use state-of-the-art data analytics technologies, like predictive analytics, to increase the effectiveness of employing intelligence data for crime prevention.
International Journal of Innovative Research & Development (GlobeEdu)
Title: Influence of Intelligence Data Utilization in Crime Prevention in Nairobi City County, Kenya
Description:
Many jurisdictions across the globe are increasingly implementing intelligence management as a strategy for crime prevention.
The study thus sought to determine the degree to which intelligence data utilization facilitates crime prevention in Nairobi City County.
The Routine Activities Theory served as a guide for the investigation.
The study population consisted of 556 criminal investigations officers (CIOs) from all Nairobi County sub-counties as well as sub-county criminal investigations heads, and a descriptive survey research technique was used.
The study used the Yamane formula to calculate a sample size of 247 criminal investigations officers and conducted a census of all CIO sub-county heads.
In order to calculate the number of officers in each sub-county whereby, stratified random sampling was utilized.
Officers chosen for the study were given semi-structured questionnaires, and data was gathered through personal interviews with CIO sub-county heads.
The Kiambu sub-county police division served as the site of the pilot research.
The data was analyzed using the Statistical Package for Social Sciences (SPSS).
The correlation analysis results revealed that there was a positive and a strong significant association between intelligence data utilization and crime prevention (r=0.
669, p=0.
000<0.
05).
The hypothesis test results show that intelligence data utilization influences crime prevention (β = 0.
619, ρ = 0.
000< 0.
05).
The study concludes that intelligence data utilization significantly and powerfully affects crime prevention in Nairobi City County.
However, Nairobi City County's current use of intelligence data for crime prevention is severely hampered by a number of significant factors.
Officers are unable to map offenders and crime scenes using predictive data or do effective crime diagnostics because they lack the necessary training in interpreting intelligence data.
The study recommends that the National Government's Ministry of Interior & Coordination adopt and use state-of-the-art data analytics technologies, like predictive analytics, to increase the effectiveness of employing intelligence data for crime prevention.

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