Aplikasi Opinion Mining dengan Algoritma Naïve Bayes untuk Menilai Berita Online

  • Daniel Pakpahan Program Studi Teknik Informatika, Politeknik Negeri Batam
  • Hilda Widyastuti Program Studi Teknik Informatika, Politeknik Negeri Batam
Keywords: opinion mining, naïve bayes, text preprocessing, classification, probabilistic models


Opinion mining is the process of understanding, extracting and processing textual data automatically to get the sentiment of information contained in an opinion sentence. One of text mining methods that can be used to solve the problem of opinion mining is the Naïve Bayes Classifier (NBC). Source data to be processed in the process of data classification is the opinion or comment on the news online. Before the opinion or comment data is processed into the classification process, the first step that must be passed is text processing. Text processing includes tokenizing, filtering, and stemming. The next stage, producing probabilistic models whose value will be used in classification process. The core process of the classification is determining the highest probability of each category. If the results indicate the probability Bayes comments for positive cate gory is larger then the comment, then the comments is categorized as a positive opinion and vice versa.


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