Twitter Tweet: Sentiment Analysis on Illegal Investment using Naive Bayes Algorithm

Abstract

In today’s era, investment is in demand by society because of its vast profits. In recent months, Indonesia has been shocked by illegal investment platforms or online trading platforms that are touted as fraudulent investments. Overcoming this problem, sentiment analysis was carried out with the help of social media Twitter. This study aims to find out and analyze people’s sentiments. It is then classified into positive, neutral, and negative sentiments. This study used the naïve Bayes method with orange application. Data collection was taken in March 2022. The survey results obtained 152 positive sentiment data, 244 negative sentiment data, and 175 neutral sentiment data with an accuracy rate of 81.069%. This means that the level of negative sentiment is greater than that of positive sentiment. With this research, it is hoped that it can benefit the public to be more careful in choosing investments.