Penentuan Metode Terbaik Analisis Sentimen Pada Twitter Pelanggaran Hukum (Korupsi Dan Pajak)

Faradilla Izzah Rahmadani; Rizki Rahmawati

doi:10.5281/zenodo.8312289

Faradilla Izzah Rahmadani Universitas Sebelas Maret
Rizki Rahmawati Universitas Sebelas Maret

DOI: https://doi.org/10.5281/zenodo.8312289

Keywords: sentiment analysis, violation of law, navie bayes, random forest, support vector machine

Abstract

A lot of topics are discussed on social media. One of the topics discussed about Twitter is violations of law in Indonesia such as corruption and taxes. Sentiment analysis is the process of extracting, understanding, and processing unstructured data to obtain sentiment information found in opinion sentences. This study was conducted to analyze public opinion towards the violation of law on the social media Twitter uses sentiment analysis. A total of 14,446 data were divided into 80% training data and 20% testing data then classified using Naive Bayes, Random Forest, and Support Vector Machine (SVM) algorithms. The calculation results show positive sentiment of 16,3%, negative sentiment of 52,3%, and neutral sentiment of 31,4%. The comparison of the three algorithms obtained using SVM algorithm gets the highest accuracy of 72%.

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