📞 +91-7667918914 | ✉️ iarjset@gmail.com
International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
ISSN Online 2393-8021ISSN Print 2394-1588Since 2014
IARJSET aligns to the suggestive parameters by the latest University Grants Commission (UGC) for peer-reviewed journals, committed to promoting research excellence, ethical publishing practices, and a global scholarly impact.
← Back to VOLUME 8, ISSUE 11, NOVEMBER 2021

CRIME ANALYSIS USING PREDICTIVE MODELING

DIVYA CHOPRA*, DEEPANSHU KAUSHIK

👁 1 view📥 0 downloads
Share: 𝕏 f in

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page CRIME ANALYSIS USING PREDICTIVE MODELING DIVYA CHOPRA*, DEEPANSHU KAUSHIK

Abstract: Preventive measures are always better than curative ones. The same is true for crimes as well. The Crime Analysis uses mathematics, predictive modeling and predictive analysis to help law enforcement in targeting potential criminal and antisocial activities. Studying, observing and analyzing the patterns formed in crimes are used in various countries and organizations. Crime is dynamic in nature but still we can find patterns in a crime which will help the authoritative and concerned organizations to find areas that are less affected by a crime and those with a high rate in a particular crime. This research aims at providing people a thought on how crime patterns can be analyzed and can help in creating a crime free neighborhood with the help of supervised learning. K-nearest neighbor algorithm was used to find locations that are vulnerable to the classified crime. As of now, we have taken six classes of crime: Robbery, Accident, Gambling, Violence, Kidnapping, and Murder. For this research the datasets were selected from government websites, which were pre processed and used to find patterns in the various classes of crime occurring in different states according to the jurisdiction of the country. KEYWORDS- Crime Analysis, Predictive Modelling, K-nearest neighbor, Supervised Learning Downloads: | DOI: 10.17148/IARJSET.2021.81135 How to Cite: [1] DIVYA CHOPRA*, DEEPANSHU KAUSHIK, "CRIME ANALYSIS USING PREDICTIVE MODELING," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: IARJSET.2021.81135 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat

How to Cite:

[1] DIVYA CHOPRA*, DEEPANSHU KAUSHIK, “CRIME ANALYSIS USING PREDICTIVE MODELING,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2021.81135

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License.