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Journal : Building of Informatics, Technology and Science

Analisis Sentimen Terhadap Program Makan Bergizi Gratis Menggunakan Algoritma Machine Learning Pada Sosial Media X Triningsih, Elsa; Afdal, M; Permana, Inggih; Rozanda, Nesdi Evrilyan
Building of Informatics, Technology and Science (BITS) Vol 6 No 4 (2025): March 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i4.6534

Abstract

The government has launched the Free Nutritious Meal Program as part of a strategic effort to reduce stunting in Indonesia. However, the program has generated a lot of controversy among the public, especially regarding the large budget allocation that is considered burdensome and its impact on the education sector and the country's financial stability. This study aims to analyze public sentiment towards the program by utilizing data from social media platform X (Twitter) as much as 2,400 data. Public sentiment is classified into three categories, namely positive, negative, and neutral, using two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest. In addition, the SMOTE technique is used to handle data imbalance in the model training process. The analysis results showed that negative sentiments dominated at 46%, with the main issue highlighted being the high budget allocation and its impact on education. In terms of performance, the SVM algorithm with SMOTE produced the highest accuracy of 85.74%, outperforming the Random Forest algorithm which only achieved 81.53% accuracy.