Applying Data Mining Techniques in Predicting Index and non-Index Crimes
Allemar Jhone P. Delima · International Journal of Machine Learning and Computing · 2019
An increasing incidence of crime has led to the development and use of computer-aided diagnosis system, tools and methods in analyzing, classifying and predicting crimes.This paper clusters municipalities in Surigao del Norte using K-Means algorithm.This is instrumental in finding identical traits, patterns and values in categorizing municipalities with much, more, and most number of recorded index and non-index crimes from 2013-2017.Prediction of its occurrence for the year 2018-2022 was also provided using ARIMA(1,0,7) model.Results showed that Surigao City has the most number of recorded index and non-index crimes.Followed by the municipality of Placer, Claver, and Dapa of cluster 2 and Del Carmen of cluster 3. Further, physical injury, homicide, violation of special laws, car napping, reckless imprudence resulting to physical injury, and other non-index crimes has 26%, 25%, 25%, 24%, 24%, and 23% forecasted increase for the year 2018-2022 with the highest occurrence in years 2018, 2018, 2020, 2018, 2020, and 2020 respectively.Future researchers may utilize other data mining techniques supported by a better accuracy result.