Implementasi Algoritma Naive Bayes Untuk Analisis Sentimen Isu Resesi Ekonomi 2023 Di Indonesia Pada Platform Twitter

Economic recession is a condition where a country experiences a decline in economic activity.The issue of the 2023 recession in Indonesia has become a hot topic of discussion since the outbreak of the war between Russia and Ukraine, the Covid-19 pandemic, and uncontrollable inflation.The emergence of this issue has generated various responses from the public, and some of them have expressed their opinions through social media, particularly Twitter.From these issues, an analysis of public sentiment towards tweets is needed to understand the response of the active Indonesian citizens regarding the 2023 Economic Recession issue.This research applies the Naive Bayes algorithm for data classification, and the process starts with data collection through scraping techniques, followed by data cleaning, splitting the data into training and testing sets, data labeling, data pre-processing, classification process, and concludes with model evaluation using a confusion matrix.The number of data collected after the data cleaning process is 3301 tweets.The obtained model accuracy is 93.46%, with a prediction of 1301 tweets having a positive sentiment, 1237 tweets having a negative sentiment, and 763 tweets being labeled as neutral sentiment.