SENTIMENT ANALYSIS OF PUBLIC COMMENTS ON THE FREE NUTRITIOUS MEAL PROGRAM USING A RULE-BASED APPROACH - Iqbal, Muhammad; Sibuea, Mustika Fitri Larasati; Harahap, Indra Ramadona (Smart Education, 2025)
Abstract: The Free Nutritious Meal Program (MBG) is a government initiative aimed at improving children’s nutrition and reducing stunting in Indonesia. This study applies a rule-based sentiment analysis approach to evaluate public opinion on the program by analyzing YouTube comments. The dataset was processed through standard text preprocessing techniques, including case folding, stopword removal, and emoji filtering. Sentiment classification was performed using a keyword-based labeling system that categorized comments into positive, negative, and neutral classes. The classification results, visualized using a bar chart, revealed that neutral sentiment dominated the overall public discourse. This suggests that most users expressed uncertainty, factual observations, or non-judgmental questions about the program. Positive sentiment followed, reflecting public support and appreciation for the initiative’s goals. In contrast, negative sentiment accounted for the smallest portion, mainly expressing concerns about food safety and implementation. This study demonstrates that a simple and interpretable rule-based model, when combined with effective preprocessing, can serve as a practical and efficient tool for large-scale public sentiment monitoring. The visualization results provide initial insights for policymakers to improve communication strategies and address public concerns regarding the MBG program. Keywords: Sentiment Analysis; Public Opinion; Free Nutritious Meal Program (MBG); Stunting Reduction; Policy Evaluation. Abstrak: Program Makan Bergizi Gratis (MBG) merupakan inisiatif pemerintah untuk meningkatkan gizi anak dan menurunkan angka stunting di Indonesia. Penelitian ini bertujuan mengevaluasi opini publik terhadap program tersebut melalui analisis komentar di platform YouTube dengan pendekatan analisis sentimen berbasis aturan (rule-based). Data dianalisis melalui tahapan preprocessing teks, seperti case folding, penghapusan stopword, dan penyaringan emoji. Klasifikasi sentimen dilakukan menggunakan sistem pelabelan berbasis kata kunci yang membagi komentar ke dalam tiga kategori: positif, negatif, dan netral. Hasil klasifikasi yang divisualisasikan dalam grafik batang menunjukkan bahwa sentimen netral mendominasi komentar publik, mencerminkan ketidakpastian, pertanyaan, atau tanggapan informatif tanpa opini eksplisit. Sentimen positif berada di urutan kedua dan menunjukkan dukungan terhadap program, sementara sentimen negatif paling sedikit, umumnya berisi kekhawatiran terkait pelaksanaan dan keamanan pangan. Temuan ini menunjukkan bahwa pendekatan klasifikasi sederhana yang dipadukan dengan preprocessing yang efektif dapat menjadi alat yang efisien untuk memantau opini publik secara luas. Visualisasi hasil dapat menjadi dasar bagi pengambil kebijakan untuk menyusun strategi komunikasi yang lebih responsif terhadap persepsi masyarakat. Kata kunci: Analisis Sentimen; Opini Publik; Program Makanan Bergizi Gratis (MBG); Pengurangan Stunting; Evaluasi Kebijakan