Teika
Vol 7 No 1 (2017): TeIKa : April 2017

ANALISIS SENTIMEN TOKOH PUBLIK MENGGUNAKAN METODE NAÏVE BAYESIAN CLASSIFICATION PADA APLIKASI TWITTER

Yusran Timur Samuel (Fakultas Teknologi Informasi, Universitas Advent Indonesia)
Kevin Jeremy Manurip (Fakultas Teknologi Informasi, Universitas Advent Indonesia)



Article Info

Publish Date
01 Apr 2017

Abstract

Social media has provided a variety of information, especially content that is subjective or reflects the opinions of people who write. Today more and more people express their opinions or opinions on community leaders such as regional leaders, officials, influential people, and so on. Social media has provided a variety of information, especially content that is subjective or reflects the opinions of people who write. Today more and more people express their opinions or opinions on community leaders such as regional leaders, officials, influential people, and so on. Sentiment analysis on the Twitter social media application there are weaknesses in the words contained in the sentence uploaded by the application user. In this case the object of the research was carried out to Ridwan Kamil with Sentiment Analysis from the people. Based on the research conducted, it was concluded that 59 training data had an accuracy of 81.3559%, and the results obtained from testing data were: 1. There were 3 data that were truly classified as having neutral sentiments, 2. There were 7 data classified really have positive sentiment, 3. And there are 2 data that really have negative sentiment.

Copyrights © 2017






Journal Info

Abbrev

teika

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media

Description

TeIKa (Teknologi Informasi dan Komunikasi) Journal invites scholars, researchers, and students to contribute the result of their studies and researches in the areas related to Information and Communication Technology work which covers Information System, Computer Networks, Computer Security, ...