Abstract
While we like to think that universities are safe and free of acts of crime, there is a need for the university police department to be present on campus. The number of crime incidents reported during the year was 225. Of the 3,990 universities and colleges that reported data on crime and protection, 3,397 of them reported fewer incidents than those reported by CSUS [1]. With the number of incidents being reported on campus, it becomes crucial to ask a few questions to the university police department like – What policies does the police department take into action for the crime incidents on campus? What prediction mechanism they currently have in place to prevent crime from taking place? How useful would it be for the department if they have a crime prediction system which not just shows the frequent crime patterns but gives the future crime occurrence for a specific location on campus? Considering the above questions and a few others, through this project, we emphasize the importance of predictive policing for on campus crime prediction for CSU Sacramento. The primary step, which plays an essential role in completing the project is the collection of data. The data we collected from the police department was in multiple hard copy binders for years from 2013-2019, which had to be digitized for us to have historical data to predict on. The goal of this project is to provide a solution on crime prediction technique to use by conducting extensive research on multiple methodologies and techniques starting from cleaning the data and pre-processing it to perform multiple data balancing techniques and then to perform crime prediction techniques which gives an accuracy closer to the industry standard of 75-80%.