Analysis of text mining clustering on suara surabaya crime report with dbscan neural network autoencoder algorithm

HIGHLIGHTS

• What: This study examines text mining on crime report data from Suara Surabaya using the DBSCAN clustering method and the Neural Network Autoencoder. The research showed that the classification using the Support Vector Machine (VCM) method produced an accuracy value of 87.14% . At this stage, the authors determine which document unit to use according to the desired implementation needs.. The aim of DBSCAN is to identify clusters in irregular data or data that do not have a precise geometric shape.
• Who: IPTEK COMP from the Statistics Study Program, Department of Mathematics, Universitas Airlangga, Surabaya . . .
  

   

  

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