Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal JURNAL INTEGRASI
Daniel Pakpahan
Program Studi Teknik Informatika, Politeknik Negeri Batam
Other

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Aplikasi Opinion Mining dengan Algoritma Naïve Bayes untuk Menilai Berita Online Daniel Pakpahan; Hilda Widyastuti
JURNAL INTEGRASI Vol 6 No 1 (2014): Jurnal Integrasi - April 2014
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 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.
Co-Authors Hilda Widyastuti