Analisis Sentimen Ibukota Negara Baru Menggunakan Metode Naïve Bayes Classifier

Dewi Aryanti

doi:10.47065/josh.v3i4.1944

Dewi Aryanti * STMIK Borneo Internasional Balikpapan, Balikpapan, Indonesia

(*) Corresponding Author

DOI: https://doi.org/10.47065/josh.v3i4.1944

Keywords: Twitter; Capital; Sentiment Analysis; Naive Bayes; Classification

Abstract

Twitter is one of the most popular social media websites on the internet today. The site covers a wide range of topics, including law, politics, culture, economics and more. On Twitter, many people talked about the idea of moving the capital of Indonesia. But there is disagreement between people regarding the discourse, because each side has different opinions and views. In order to understand the process of data automatically extracted from unstructured texts, then sentiment analysts were developed. This process is used to determine the overall opinion of a population about a subject in public discourse, as can be derived from diverse opinions on Twitter. In the application of sentiment analysis, the study used the naïve bayes method to be applied to tweets of new capital topics for the purpose of class classification of sentiment on social media tweeters. Technical classification is carried out by classifying into 2 classes, namely positive and negative. Based on the results of testing conducted on the new capital's sentiment tweets from social media twitter as many as 1,065 tweets tested sentiment about the new capital from social media twitter 289 stated positive and 776 stated negative Naïve Bayes method obtained accuracy = 94.18%,)

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