Spatial distribution of crime in Sumatra and java using unsupervised learning algorithm Available to Purchase

Indonesia has a low Human Development Index, indicating that the country still has a long way to go in terms of improving its general quality of life and health. Furthermore, Indonesia is afflicted by a number of socioeconomic difficulties, such as overpopulation, poverty, excessive unemployment, and a deficient education system. This issue has the potential to have negative consequences for our society, such as an increase in crime rates. In the subject of criminal statistics, many indicators are commonly used to measure crime from a broader perspective as well as the level of severity. This study aims to characterize the distribution of overall crime rates among Indonesia’s provinces, with a special focus on Sumatra and Java. Statistics supplied by the Central Bureau of Statistics for the years 2010-2020 about the number of crimes recorded by regional police officers. The unsupervised learning technique is used, with K-means as the classification algorithm, to categorize objects observed in each state into groups that are related to one another. As a result, the provinces of Bengkulu, the Bangka Belitung Islands, and Banten became the lowest clusters; as a result, it is reasonable to state that these three provinces had the lowest crime rates in contrast to the other provinces in Sumatra and Java between 2010 and 2020.