Aplikasi Opinion Mining dengan Algoritma Naïve Bayes Untuk Menilai Berita Online
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Date
2015-01-31
Authors
Pakpahan, Daniel
Journal Title
Journal ISSN
Volume Title
Publisher
Politeknik Negeri Batam
Abstract
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 of 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 no such
tokenizing the text preprocessing, filtering, and stemming. The next stage is to
produce probabilistic models whose value will be used in the classification process.
The process is the core of the classification process to determine the highest
probability of each category. If the results indicate the probability Bayes comments
for positive category is larger then the comment is categorized as a positive opinion
and vice versa.
Keywords: opinion mining, naïve bayes, text preprocessing, classification,
probabilistic models
Description
Keywords
Teknik Informatika, Informatika, Ilmu Komputer, Pengetahuan, Sistem, Application, News Online