Mitigating vulnerabilities through forecasting and crime trend analysis
Markdy Y. Orong, Ariel M. Sison, Alexander Arcenio Hernandez · 2018 5th International Conference on Business and Industrial Research (ICBIR) · 2018
The study clustered the indexed crime data of the province of Misamis Occidental, Philippines and provided a prediction of its occurrence in the next five years. The study utilized the k-means clustering algorithm and Autoregressive Integrated Moving Average (ARIMA) model to cluster and forecast the indexed crime data respectively. Results showed that 3 of the indexed crime data were in the first group and five are in the second group. Moreover, rape, cattle rustling, physical injury, robbery, and theft showed an increasing pattern based on the forecasted data from 2015 to 2020. On the other hand, murder showed a decreased pattern based on the predicted data from 2015 to 2020. Homicide and carnapping showed the unpredictable behavior of forecasted data in each predicted year. Future research endeavors may utilize other clustering and forecasting algorithms and conduct a comparative study on the different results.