Identifying Crime Hotspots in CAMANAVA by Geographic Information System using Spatio-Temporal Analysis

Hotspots in crime analysis are regions that require attention from law enforcement, perhaps through increased allocation of resources or location-specific patrolling custom-made to hotspot features. The purpose of the study was to develop a graphical information system (GIS) which identifies the different hotspots of crimes that occurred in the year 2017 throughout the cities of Caloocan, Malabon, Navotas and Valenzuela (CAMANAVA) using MarkerClusterer clustering algorithm along with spatial and temporal analysis to cluster occurrence of crime together in certain areas and periods, and to provide a recommendation for that hotspot. The developmental research design was adopted by the proponents to satisfy the research problem, along with the Knowledge Discovery in Database (KDD) during the development of the system. Nine (9) crime types were observed, namely; car/motor-napping, drug-related incidents, homicide, murder, physical injuries, rape, robbery, theft and vehicular accidents. A total of 12,784 occurrences of crimes was observed, and vehicular traffic accident occurred the most which accounts for 63.97% of the total 12,639 crime occurrences in CAMANAVA during the year 2017. Hourly distribution varied depending on the crime observed, daily distribution did not show much variation, but monthly distribution showed that August is the month when most crimes occurred. The proponents recommend that future research may include impact of socioeconomic and environmental factors in crimes, plus data mining techniques that could be able to forecast crime based on the hotspots that were generated.

Keywords – Crime Hotspots, Spatio-Temporal Analysis, Geographic Information System (GIS), MarkerClusterer Algorithm, CAMANAVA Crimes