Sentiment Analysis from Twitter Regarding E-SIM Services by Smartfren Using the Naïve Bayes Classifier Method

Abstract

Smartfren is a provider of internet, mobile phone, and Android-IOS smartphones that offers faster and more affordable services in Indonesia. E-SIM is a digital SIM that enables the activation of cellular packages from network operators without the need for a physical nano-SIM. Smartfren provides E-SIM services, making it the first provider to offer this service. Consequently, numerous tweets discussing this provider have emerged, resulting in a substantial amount of Twitter data related to Smartfren. This data can be leveraged for sentiment analysis. However, the tweets often contain ambiguous or unrevealing information, making them challenging to be properly classified, especially when using the Naïve Bayes Classifier as the classification method, as observed in previous studies. Nevertheless, employing appropriate methods can generate highly valuable insights for relevant stakeholders. This research aims to analyze public opinion regarding the services provided by Smartfren, using the Naïve Bayes Classifier method. The study is intended to provide comprehensive analytical results for the related provider, allowing for a thorough understanding of the sentiment analysis. Keywords : Sentiment Analysis, Smartfren, Naïve Bayes