Analysis of Crime Detection using Data Mining Techniques

An approach for crime detection in India using Data mining techniques is proposed in this paper. The approach consists of the following steps - Data pre-processing, clustering, classification and visualization. Data mining techniques are often applied to Criminology as it provides good results. Criminology is a field which studies about various crime characteristics. Analyzing crime data means exploring crime data. Crime is identified using k-means clustering and the clusters are formed based on the similarity of the crime attributes. The Random Forest algorithm and Neural networks are applied on the data for classification. Visualization is achieved using the Google marker clustering and the crime spots are marked on the India map. The accuracy is verified using WEKA tool. This approach will benefit the Crime department of India in analyzing crime with better prediction. The paper focuses on the crime analysis of various Indian states and union territories during 2001 to 2012.

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Crime Detection Using Data Mining Techniques

SSRN Electronic Journal ◽

10.2139/ssrn.3770477 ◽

2021 ◽

Author(s):

Sumon Rony ◽

Sagor Chandra Bakchy ◽

Hadisur Rahman

Keyword(s):

Data Mining ◽

Data Mining Techniques ◽

Crime Detection ◽

Using Data

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Crime Detection using Data Mining Techniques

Computer Science & Engineering An International Journal ◽

10.5121/cseij.2020.10501 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1-5

Author(s):

Md. Sumon Rony ◽

Sagor Chandra Bakchy ◽

Hadisur Rahman

Keyword(s):

Data Mining ◽

Law Enforcement ◽

Criminal Activity ◽

Law Enforcement Agencies ◽

Data Mining Techniques ◽

Data Mining Approach ◽

Collection Data ◽

Crime Detection ◽

Phase Data ◽

Using Data

As crime rates keep spiraling each day, new challenges are faced by law enforcement agencies. They have to keep their on the lookout for any signs criminal activity. The law enforcement agencies should therefore be able to predict such increase or decrees or trends in crime. Such as theft, Killing. Crime that may occur in a particular area in a particular month, year, any timespan. Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine learning, artificial intelligence, statistical. Many algorithms for data mining approach to help detect the crimes patterns. Data Collection, Data Preprocessing Phase, Data Filtering, Linier Regression. Wekasoft are used for collection of data analyzing. Visualization finally get results. The advantage of using this tool is that clustering will be performed automatically.

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Crime detection and criminal identification in India using data mining techniques

AI & Society ◽

10.1007/s00146-014-0539-6 ◽

2014 ◽

Vol 30 (1) ◽

pp. 117-127 ◽

Cited By ~ 32

Author(s):

Devendra Kumar Tayal ◽

Arti Jain ◽

Surbhi Arora ◽

Surbhi Agarwal ◽

Tushar Gupta ◽

...

Keyword(s):

Data Mining ◽

Data Mining Techniques ◽

Crime Detection ◽

Using Data

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Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i11.468 ◽

2017 ◽

Vol 7 (11) ◽

pp. 79

Author(s):

Sujata Mulik

Keyword(s):

Data Mining ◽

Crop Yield ◽

Crop Production ◽

Climatic Factors ◽

Crop Productivity ◽

Yield Prediction ◽

Data Mining Techniques ◽

Agriculture Sector ◽

Using Data ◽

Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction. The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops.

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