Sentiment Analyisis On Twitter Social Media Towards Minahasa Using Naive Bayes Algorithm

Abstract

Sentiment analysis on social media is an effort to understand the opinions, attitudes, and emotions contained in content shared online. The study focused on sentiment analysis o f Minahasa, an area located in North Sulawesi using data obtained from the social media platform Twitter. Through the use of the Naïve Bayes algorithm, this approach aims to understand and analyze sentiment patterns associated with Minahasa. The Naïve Bayes method used in this study is a classification technique that bases its predictions on probabilities and assumptions about the independence of observed features. By utilizing text data from tweets related to Minahasa, the algorithm can classify the sentiment of each tweet into positive, negative, or neutral. This analysis allows for a deeper understanding of people's views reflected in online conversations. The data obtained from Twitter amounted to 915 tweet data which was then analyzed so as to get a variety of negative, positive and neutral sentiments.

GS Cited Analysis