Abstract

Crime is a major problem in all societies, impacting the economic and social lives of individuals and communities. Therefore, it is important to study and analyze the influencing factors and the various relationships between the motives for different crimes to prevent their recurrence in the future. Crime prediction is a method of studying the causes and motives of crime and predicting the times and places of its occurrence to reduce the occurrence of expected crimes in the future. This study aims to analyze the Los Angeles dataset and investigate the impact of certain factors on the crime rate. We used Time-series forecasting to predict future crime trends. Among Time-series forecasting models, we used SARIMA (Seasonal Auto Regressive Integrated Moving Average) and Prophet model to predict the future crime rate. The study succeeded in extracting some results by analyzing a set of factors (social and economic) that affect crime rates. The study also succeeded in training the model to predict future crimes for the years 2026 and 2027 by using historical data from 2020 to February 2025 to train the model.

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