Journal of Cybersecurity and Information Management
  JCIM
  2690-6775
  2769-7851
  
   10.54216/JCIM
   https://www.americaspg.com/journals/show/533
  
 
 
  
   2019
  
  
   2019
  
 
 
  
   K-means Clustering Analysis of Crimes on Indian Women
  
  
   MBA in Technology Management in Computer Engineering, School of Technology Management and Engineering, NMIMS University, Mumbai India
   
    Rishabh
    Singh
   
   MBA in Technology Management in Computer Engineering, School of Technology Management and Engineering, NMIMS University, Mumbai, India
   
    Rishabh
    Reddy
   
   B. Tech in Data Science, School of Technology Management and Engineering, NMIMS University, Mumbai, India
   
    Vidhi
    Kapoor
   
   Assistant Professor, Computer Engineering, School of Technology Management and Engineering, NMIMS University, Mumbai India  and a  PhD research Scholar, Symbiosis International University, Pune, India
   
    Prathamesh
    Churi
   
  
  
   Violence against women is seen as sexual or physical activity committed against women. In India, general forms of violence against women in India includes cruelty by relatives, dowry, rape, sexual assault, kidnapping, immoral trafficking, molestation etc. The security of the women is the utmost priority of any government in this world. In India, many policies and laws have been enforced to ensure the safety against women. Technology is being the biggest supporter to the government in this context. Data mining allows various techniques such as clustering classification, regression provides analysis in any form of data and helps intelligent predictions on the given dataset. In this paper, we use k-means clustering analysis on women crime dataset. As a part of pre-processing, we collated the data entries which had crime cases against women and made women crime sub-dataset from the real dataset. We then applied K means clustering for further analysis. We used a rapid miner tool for clustering analysis as it is widely used for clustering purposes. After completion of clustering analysis, we proposed our views and discussions on the clustering results. At the end, we ended up giving the futuristic work to be further done on the derived dataset we made and made available on public repositories.
  
  
   2020
  
  
   2020
  
  
   05
   25
  
  
   10.54216/JCIM.040101
   https://www.americaspg.com/articleinfo/2/show/533