Mapping Criminal Location Entity from Indonesian Online Newspapers

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    The aim of this study is to extract entity locations on crime news in Indonesian online newspapers and to tag the locations into a map. The methods used in this study are rule-based algorithm, for identifying and extracting entity location of the crime, and SVM (Support Vector Machine) algorithm, for classifying which sentence containing the location of the crime. Every sentence containing criminal location was included in geocoding process so it could be mapped into a digital map. The accuracy of identifying the entity location by using rule-based algorithm is 96.2%. SVM model that has the best accuracy in classifying sentences that contains entity scene of the crime is Radial kernel whose accuracy is 95.77%.

     

     

     

  • Keywords


    Crime; Geocoding; Information Extraction; Rule Based Algorithm; Support Vector Machine.

  • References


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Article ID: 24415
 
DOI: 10.14419/ijet.v7i4.40.24415




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