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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Sujana, Mirlan
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Mathematics

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Sentiment Analysis of Indonesia’s Free Nutritious Meal Program on X Using SVM and Random Forest Hasyim, Ferdy Aliansyah; Mahenindra, Talenta Parfaibya; Sriwahyuni, Lilis; Shapira, Alika Azka; Wigawijayanti, Wigawijayanti; Ghaisani, Nadhifa Zahra; Sujana, Mirlan; Nurdiati, Sri; Najib, Mohamad Khoirun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.40717

Abstract

The Free Nutritious Meal (Makan Bergizi Gratis/MBG) Program was introduced to address stunting in Indonesia, yet its implementation has sparked diverse public debate. This study aims to map public perception on social media X and compare the performance of Support Vector Machine (SVM) and Random Forest algorithms in sentiment classification. Utilizing a large-scale dataset of 7,452 tweets collected via stratified random sampling from January to October 2025, this research applies TF-IDF feature extraction and SMOTE data balancing. The analysis reveals that positive sentiment dominates at 47.62%, while negative sentiment accounts for 39.8\%, and neutral for 12.57%. In model comparison, SVM without SMOTE achieved the best performance with 80.66% accuracy and an F1-Score of 79.79%, outperforming Random Forest, which only reached a maximum accuracy of 72.23% after SMOTE application. These findings provide an objective overview of MBG policy acceptance and methodological insights into the effectiveness of SVM in handling high-dimensional text data.
Co-Authors Ghaisani, Nadhifa Zahra Hasyim, Ferdy Aliansyah Mahenindra, Talenta Parfaibya Najib, Mohamad Khoirun Shapira, Alika Azka Sri Nurdiati Sriwahyuni, Lilis Wigawijayanti, Wigawijayanti