PENERAPAN MODEL K-MEAN CLUSTERING UNTUK MENGOPTIMALKAN KELAS DATA TRAINING PADA ALGORITMA K-NN CLASSIFICATION

  • Bahar Bahar
  • Soegiarto Soegiarto
Keywords: classification, clustering, K-Means algorithm, K-NN algorithm, Knowledge Base

Abstract

Classification algorithm model that uses standard logic to generate a knowledge base has a weakness, namely the training data sets tends to be forced to enter the class of a particular data set up already, so often an object class of the data did not reflect fully the nature of the existing classes (unnatural), this resulted in the classification process will be less accurate. This article formulates a model of classification using clustering algorithm for the establishment of a naturally training class data as Knowledge Base System, so as to solve the problems on the training data modeling techniques that produces an object class which tends to be imposed.

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Published
2016-10-29
Section
Articles