Edi Winarko, M. Sc., Ph. D.

  • 26 January 2017, 04.34
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Email : ewinarko@ugm.ac.id
Education Background :
  • Doctor, Faculty of Computer Science, University of Flinders University, Australia.
    Thesis : –
  • Master, Faculty of Computer Science, Queen’s University, Canada.
    Thesis : –
  • Undergraduate, Statistics, FMIPA, UGM, Indonesia.
    Thesis : –
Research Interest :
  • Data Mining, Machine Learning, Information Retrieval
Research Cluster/Group :
  • Computer Science
List of Publications :
  • Karyawati, E., Winarko, E., Azhari and Harjoko, A. (2015). Ontology-based Why-Question Analysis Using Lexico-Syntactic Patterns. International Journal of Electrical and Computer Engineering (IJECE), Vol. 5, No. 2.
  • Wiranto, Winarko, E., Hartati, S. and Wardoyo, R. (2014). Improving the Prediction Accuracy of Multicriteria Collaborative Filtering by Combination Algorithms. International Journal of Advanced Computer Science and Applications, Vol. 5, No. 4, Page 44-51.
  • Sembiring, I., Istiyanto, J.E, Winarko, E. and Ashari, A. (2013). Payload Attribution Using Winnowing Multi Hashing Method. International Journal of Information and Network Security (IJINS), Vol. 2, No. 5, Page 360-370.
  • Nurwidyantoro, A., and Winarko, E. (2012). Parallelization of Maximum Entropy POS Tagging for Bahasa Indonesia with MapReduce, International Journal of Computer Science Issues (IJCSI), Vol 9, Issue 4, July 2012.
  • Hakim, R.B.F, Subanar, and Winarko, E. (2011). Reducing Dendogram Instability using Clustering Based on Indiscernibility and Indiscernibility Level. International Journal of Granular Computing, Rough Sets and Intelligent Systems (IJGRSIS), Vol 2, No.2, Page 87-106.
  • Hakim, R.B.F, Subanar, and Winarko, E. (2010). The Concept of Indiscernibility Level of Rough Set to Reduce the Dendrogram Instability. Database Theory and Application, Bio-Science and Bio-Technology: Communications in Computer and Information Science, Vol 118.
  • more..