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All Journal JOINCS (Journal of Informatics, Network, and Computer Science)
Ika Ratna Indra Astutik
Program Studi Informatika, Universitas Muhammadiyah Sidoarjo
Computer Science & IT

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Analysis of Community Sentiments Regarding Plans to Relocate National Capital Using the Naïve Bayes Method Tomi Eko Hidayat; Mochamad Alfan Rosid; Ika Ratna Indra Astutik
JOINCS (Journal of Informatics, Network, and Computer Science) Vol 3 No 2 (2020): November
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (291.837 KB) | DOI: 10.21070/joincs.v4i0.712

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%.
Co-Authors Mochamad Alfan Rosid Tomi Eko Hidayat