10th Annual International Conference on Industrial Engineering and Operations Management

Event of Crime against Property: Robbery & Theft Prediction using Probabilistic Graphical Model

REX AURELIUS ROBIELOS
Publisher: IEOM Society International
0 Paper Citations
1 Views
1 Downloads
Track: Operations Research
Abstract

This study analyzed the occurrence of robbery and theft in the City of Manila using discrete Bayesian network model.    Using a 5-year data of robbery and theft in the City of Manila (with conviction), the results showed that February and July emerged as the months with highest probability of crime happening at 10.66 percent and lowest on April with 6.80 percent.  In terms of crime happening on a week, the highest probability occurred on the 2nd week with 28.3 percent and lowest on the 5th week at 6.8 percent.  Most of the crimes happened between 3PM to 6PM with 17 percent and lowest occurrence between 6AM to 9AM at 7.0 percent.  Male population are more likely to be a victim of crime in almost all of the identified locations except for Pandacan where female population has a higher probability at 53 percent.  With these information, a patrol priority location table was developed to show the location where the crime is more likely to happen in a particular time range of the day.  This information can help the Philippine National Police in the police resource deployment.    

Published in: 10th Annual International Conference on Industrial Engineering and Operations Management, Dubai, United Arab Emirates

Publisher: IEOM Society International
Date of Conference: March 10-12, 2020

ISBN: 978-1-5323-5952-1
ISSN/E-ISSN: 2169-8767