Published In : IJCSN Journal Volume 6, Issue 4

Date of Publication : August 2017

Pages : 489-494

Figures :03

Tables : 05

 

Md. Abdul Awal : Department of Computer Science and Engineering, Khulna University of Engineering & Technology (KUET), Khulna 9203, Bangladesh.

Jakaria Rabbi : Department of Computer Science and Engineering, Khulna University of Engineering & Technology (KUET), Khulna 9203, Bangladesh.

Imran Rana : Department of Computer Science and Engineering, Khulna University of Engineering & Technology (KUET), Khulna 9203, Bangladesh.

 

Data Mining, Crime Forecasting, Linear Regression, Gradient Descent

At present, Data mining has become a vital part of crime detection and prevention in many countries. There are other applications of data mining in the domain of law enforcement such as determining criminal "hot spots", creating criminal profiles, and learning crime trends to hold the pledge of abating crime related problem. In this paper, data mining technique is used to forecast future crime trends of Bangladesh. For this purpose, linear regression model is trained by crime data of previous years. After training linear regression, different types of crime are forecasted for the year of 2018. All the results are shown through the table 2 to table 5. Table 1 shows that, how accurate the liner regression is to forecast future crime trends of Bangladesh. From the experimental result it is also seen that, most of the crimes are increasing with the growth of population. The results of this data mining could potentially be used to lessen and even prevent crime for the forthcoming years. The extension of this research work is to forecast the location of crime occurrence, so that prior actions can be taken to prevent crime.

 

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