Open AccessAnalysis sentiment in social media against election using the method naive Bayes
Author(s) -
Damar Nurcahyono,
Willy Permana Putra,
Abdul Najib,
Tien Rahayu Tulili
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1511/1/012003
Subject(s) - mindset , sentiment analysis , democracy , social media , variety (cybernetics) , naive bayes classifier , big data , politics , political science , psychology , general election , social psychology , sociology , computer science , artificial intelligence , data mining , law , support vector machine
Election is the process of selecting people to fill a variety of political positions that are diverse. General elections in a country are usually held periodically where the country adheres to a democratic system. Indonesia is a country that adopts a democratic system. The development of the use of Social Media is very fast. Nowadays, there are many social media which have a big influence. As a result, society has experienced changes in culture, ethics, norms and a more critical mindset in responding to existing conditions as well. Social media is now increasingly easy to use by all groups, from the beginning only a small person to a successful person and famous for Social Media. Sentiment analysis is a science that is useful for analyzing someone’s opinions, sentiments, and emotions expressed in the text. In this study the Naïve Bayes method can be applied to the classification of positive, negative, and neutral opinions. In this study of 50 training data and 10 test data obtained an accuracy of 90%. And the results obtained positive sentiment percentage of 50%, negative 20%, neutral 10%. More positive sentiments gained.