ANALISIS SENTIMEN OPINI PUBLIK TERHADAP RUU CIPTA KERJA PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER

AMARYANSYAH, TAUFIK (2021) ANALISIS SENTIMEN OPINI PUBLIK TERHADAP RUU CIPTA KERJA PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER. Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

TAUFIK AMARYANSYAH Program Studi Informatika, Fakultas Sains & Teknologi Universitas Teknologi Yogyakarta Jl. Ringroad Utara Jombor Sleman Yogyakarta E-mail: taufik.amary@gmail.com ABSTRACT RUU Cipta Kerja is a draft law containing job creation and empowerment of micro, small and medium enterprises. RUU Cipta Kerja also aims to advance economic growth in Indonesia. However, not a few Indonesians reject the draft law because it causes public controversy, so that there are many opinions on social media, especially on Twitter. With so many opinions, it is indeed very time consuming to see how big the pros and cons of society are of the bill. Therefore, it is necessary to classify public opinion into positive or negative opinions automatically, commonly known as sentiment analysis. This study aims to create a sentiment analysis system about public opinion on RUU Cipta Kerja and find out how accurate it is. The method used in this study, for data preprocessing using case folding, cleaning, tokenizing, filtering, unique character removing, and stemming, for weighting using TF-IDF, and for the classification process using the Naïve Bayes Classifier method. The data used are tweets in Indonesian with the keyword RUU Cipta Kerja. This study analyses public opinion sentiment towards RUU Cipta Kerja with an accuracy of 79%, a precision value of 89%, and a recall of 82%. Keywords: Sentiment Analysis, RUU Cipta Kerja, TF-IDF, Naïve Bayes Classifier

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 07 Sep 2021 05:02
Last Modified: 07 Sep 2021 05:02
URI: http://eprints.uty.ac.id/id/eprint/8008

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