Sentiment Analysis of Twitter Towards the Free Lunch Program Using the C4.5 Algorithm - Hanin, Allamanda Salsabila; Maryam, Maryam (International Journal of Advances in Data and Information Systems, 2025)
This study analyzes public sentiment towards the Makan Siang Gratis (Free Lunch) Program on social media X using the C4.5 algorithm. This program, which was initiated as a campaign promise in the 2024 Election, aims to provide free nutritious food for school students in Indonesia. Given the high public interaction on social media, this study was conducted to determine the public response to the program, which can be positive, neutral, or negative sentiment. The methods used include data collection from social media X, text pre-processing, sentiment labeling, application of Term Frequency-Inverse Document Frequency (TF-IDF), and model evaluation with accuracy metrics. The dataset consists of 3,344 tweets which are then classified using the C4.5 algorithm. Based on the evaluation results, it produces an average precision value of 79%, recall of 76%, F1-score of 77%, and is able to provide an accuracy of 78%. Thus, this model shows effective performance in classifying public sentiment. This study can contribute to the use of social media sentiment analysis as a tool for public policy evaluation.