JOINCS (Journal of Informatics, Network, and Computer Science)
Vol 3 No 2 (2020): November

Analysis of Community Sentiments Regarding Plans to Relocate National Capital Using the Naïve Bayes Method

Tomi Eko Hidayat (Program Studi Informatika, Universitas Muhammadiyah Sidoarjo)
Mochamad Alfan Rosid (Program Studi Informatika, Universitas Muhammadiyah Sidoarjo)
Ika Ratna Indra Astutik (Program Studi Informatika, Universitas Muhammadiyah Sidoarjo)



Article Info

Publish Date
30 Nov 2020

Abstract

This study aims to analyze sentiment towards the transfer of new capitals derived from comments on the tweeter. The method used in this research is Naïve Bayes Classifier, a classic method that has a pretty good accuracy. Naive Bayes Classifier is a probabilistic classification based on the Bayes theorem, taking into account naïv independence assumptions. In addition to using the naïve bayes method, in this study the researchers also used word weighting. The weighting word used is TF-IDF, which is a combination of term frequency and inverse document frequency. By using 3 testing methods, namely Confusion matrix, Precission and Recall, and K-Fold Cross Validation. The results obtained in this study are 3 document classifications, namely Positive, Negative and Neutral. Testing is done by dividing the document into 2 subsets, namely training data and test data and the resulting accuracy of 64.6%.

Copyrights © 2020






Journal Info

Abbrev

joincs

Publisher

Subject

Computer Science & IT

Description

JOINCS publishes original research papers in computer science and related subjects in system science, with consideration to the relevant mathematical theory. Applications or technical reports oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the ...