Analysis of Document Clustering based on Cosine Similarity and K-Main Algorithms

  • Bambang Krismono Triwijoyo Universitas Bumigora
  • Kartarina Kartarina Universitas Bumigora
Keywords: document clustering, cosine similarity, k-main


Clustering is a useful technique that organizes a large number of non-sequential text documents into a small number of clusters that are meaningful and coherent. Effective and efficient organization of documents is needed, making it easy for intuitive and informative tracking mechanisms. In this paper, we proposed clustering documents using cosine similarity and k-main. The experimental results show that based on the experimental results the accuracy of our method is 84.3%.


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Author Biography

Kartarina Kartarina, Universitas Bumigora

Lecturer at Information Technology Departement, Bumigora University 


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How to Cite
Triwijoyo, B., & Kartarina, K. (2019). Analysis of Document Clustering based on Cosine Similarity and K-Main Algorithms. Journal of Information Systems and Informatics, 1(2), 164-177.