Public Sentiment toward Indonesia's Free Nutritious Meal Program on X: A Systematic Review
DOI:
https://doi.org/10.55927/dnfcvw62Keywords:
Public Sentiment; Free Nutritious Meal; Social Media X; Digital Communication; Systematic Literature ReviewAbstract
This study regularly reviews research on public sentiment toward Indonesia's Free Nutritional Food (MBG) program expressed on X/Twitter. Using the PRISMA 2020 framework, literature published between 2024 and 2026 was identified through Google Scholar and GARUDA, resulting in 30 empirical studies included in the final review. The data were synthesized descriptively and narratively by examining sentiment patterns, recurring issues in public responses, and methodological variations across studies. The findings show that public sentiment toward MBG is heterogeneous. Positive sentiment was reported more frequently, but substantial negative, neutral, and polarized responses were also identified. Positive responses were mainly associated with expected nutritional and social benefits, while critical responses focused on implementation, distribution, food safety, budget management, transparency, and accountability. Differences in reported sentiment were also linked to variations in data-collection periods, dataset sizes, labeling procedures, classification models, preprocessing techniques, and sentiment categories. This review contributes a communication perspective by moving beyond algorithm performance to explain how MBG is discussed and evaluated within digital public discourse on X
References
Ainur, Latifah, & Nugraha. (2025). Analisis Sentimen Publik Terhadap Program Makan Bergizi Gratis Menggunakan Metode Random Forest Pada Platform X. https://doi.org/10.24176/sitech.v8i1.15628
Alkadri, Rhendy, & Insani. (2026). Sentiment Analysis of X Users’ Opinions on the Free Nutritious Meal (MBG) Program Using Support Vector Machine. https://doi.org/10.66314/joresd.v4i1.1094
Ariani, Norhikmah, & Pristyanto. (2026). Evaluasi Komparatif Algoritma Machine Learning dalam Analisis Sentimen Program Makan Bergizi Gratis di Media Sosial X. https://doi.org/10.30865/jurikom.v13i3.9741
Arif, & Kustiyono. (2025). Analisis Sentimen Kebijakan Makan Bergizi Gratis di Media Sosial Menggunakan Natural Language Processing Berbasis Python TextBlob di Indonesia. https://doi.org/10.52436/1.jpti.931
Ati, & Prasetyaningrum. (2025). Analysis of Community Sentiment Towards Free Nutrition Meal Programs on Twitter Using Naïve Bayes, Support Vector Machine, K-Nearest Neighbors, and Ensemble Methods. https://doi.org/10.51519/journalisi.v7i2.1098
Ceron, A., & Negri, F. (2016). The “Social Side” of Public Policy: Monitoring Online Public Opinion and Its Mobilization During the Policy Cycle. Policy & Internet, 8(2), 131–147. https://doi.org/10.1002/poi3.117
Chandra, & Dewi. (2026). Analisis Sentimen Terhadap Program Makan Bergizi Gratis Pada Media Sosial X Menggunakan Metode Naive Bayes Classifier. https://doi.org/10.24036/w6zjmv19
Farizi, Hendriadi, & Ridha. (2026). Analisis Sentimen Program Makan Bergizi Gratis pada Media Sosial X dengan Algoritma Support Vector Machine. https://doi.org/10.23960/jitet.v14i3.10195
Fatkhurrohman, Nugroho, & Fadillah. (2025). Analisis Sentimen Program Makan Bergizi Gratis Pemerintah RI Melalui Twitter Menggunakan Metode SVM. https://doi.org/10.31004/riggs.v4i3.2533
Haerani. (2026). Analisis Sentimen Program Makan Bergizi Gratis Berdasarkan Komentar di Media Sosial X Menggunakan GRU. https://doi.org/10.23960/jitet.v14i1.8754
Hasyim. (2026). Sentiment Analysis of Indonesia’s Free Nutritious Meal Program on X Posts Using SVM and Random Forest. https://doi.org/10.18860/cauchy.v11i1.40717
Hermansyah, & Hasibuan. (2025). Sentiment Analysis of Free Nutritious Meal Programme on Social Media X using Linear Regression and Random Forest Algorithms. https://doi.org/10.33558/piksel.v13i1.10633
Ihdahayuningsih. (2026). Analisis Sentimen Masyarakat Terhadap Program Makan Bergizi Gratis Pada Media Sosial X Dengan Naïve Bayes. https://doi.org/10.62357/jsit.v5i1.929
Ilham, & Kartikadarma. (2026). Sentiment Analysis of Free Nutritious Meal Program on Platform X: Comparing Naive Bayes, SVM, Random Forest, and IndoBERT. https://doi.org/10.30871/jaic.v10i3.12959
Manao, & Mujiyono. (2026). Sentiment Analysis of the Free Nutritious Meal Program on Twitter Using Naive Bayes and IndoBERT-Based Labeling. https://doi.org/10.63158/journalisi.v8i1.1345
Mellon, J., & Prosser, C. (2017). Twitter and Facebook are not representative of the general population: Political attitudes and demographics of British social media users. Research & Politics, 4(3), 1–9. https://doi.org/10.1177/2053168017720008
Muhabbab, Bunyamin, & Hasmawati. (2025). Sentiment Analysis of Indonesia’s Free Nutritious Meal Program on Platform X (Formerly Twitter) Using IndoBERT. https://doi.org/10.30829/zero.v9i3.27629
Mukhlisin, M., Berlilana, B., & Saputro, R. E. (2026). Literature Review: Comparison of Machine Learning Algorithms for Sentiment Analysis of Free Nutritious Meals. SISTEMASI: Jurnal Sistem Informasi, 15(3), 1110–1120. https://doi.org/10.32520/stmsi.v15i3.6201
Munir, R. A., & Voutama, A. (2025). Analisis Sentimen Cuitan di Media Sosial X Tentang Program Makan Bergizi Gratis dengan Metode NLP. Jurnal Informatika Dan Teknik Elektro Terapan, 13(3). https://doi.org/10.23960/jitet.v13i3.6912
Mursyid, Setiawan, & Arifin. (2026). Implementation of IndoBERT in Sentiment Analysis of Free Nutritious Meal Programs on the X Social Media Platform. https://doi.org/10.24036/jtip.v19i1.1104
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Pratama, Achmadi, & Sari. (2026). Analisis Sentimen terhadap Makan Bergizi Gratis pada Sosial Media X Menggunakan Metode Decision Tree dengan Pembanding Naive Bayes. https://doi.org/10.36040/jati.v9i6.15525
Prianto, Berlilana, & Saputro. (2026). Comparative Performance Analysis of Random Forest and Logistic Regression for Sentiment Classification of the Makan Bergizi Gratis Program on Platform X. https://doi.org/10.63158/journalisi.v8i1.1371
Putri, & Novianto. (2026). Analisis Sentimen Masyarakat Indonesia terhadap Program Makan Bergizi Gratis (MBG) di Media Sosial X Menggunakan Perbandingan Algoritma Naive Bayes dan Support Vector Machine. https://doi.org/10.36040/jati.v10i3.18441
Ramadhan, & Khoirunnisa. (2025). An Integrated Random Forest for Analyzing Public Sentiment on the “Makan Bergizi Gratis” Program. https://doi.org/10.51519/journalisi.v7i3.1184
Rathore, A. K., Kar, A. K., & Ilavarasan, P. V. (2017). Social Media Analytics: Literature Review and Directions for Future Research. Decision Analysis, 14(4), 229–249. https://doi.org/10.1287/deca.2017.0355
Retnosari, Hartanti, & Sari. (2026). Perbandingan Metode Naïve Bayes dan Support Vector Machine dalam Analisis Sentimen Program Makan Bergizi Gratis pada Media Sosial X. https://doi.org/10.36040/jati.v10i4.18689
Sari. (2026). Sentiment Analysis of the Free Nutritious Meal or Makan Bergizi Gratis (MBG) Program on Social Media X from the Perspective of the Political Economy of Development. https://doi.org/10.55942/pssj.v6i6.2023
Silaban, Simatupang, & Sipayung. (2026). Public Sentiment Analysis of Free Nutritious Meal Program Discourse on Social Media X Using Support Vector Machine N-Gram Features Based. https://doi.org/10.31253/te.v9i2.4355
Stieglitz, S., Mirbabaie, M., Ross, B., & Neuberger, C. (2018). Social media analytics – Challenges in topic discovery, data collection, and data preparation. International Journal of Information Management, 39, 156–168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002
Subarkah. (2025). Sentiment Perspective of Government’s Free Nutritious Meal Policy on Social Media X using Indo-BERT and Bi-LTSM. https://doi.org/10.37802/joti.v7i2.1065
Sulistyo, & Setiadi. (2025). Analisis Sentimen Kebijakan Makan Bergizi Gratis Menggunakan IndoBERT dan Machine Learning. https://doi.org/10.37859/jf.v15i3.10546
Sultoni, A., Putra, D. A., Wahidah, H. N., Arief, M. M., R.M., P. J. P., & Utami, S. B. (2025). Public Sentiment Analysis and Distribution Optimization of Indonesia’s Makan Bergizi Gratis (MBG) Program. Jurnal Matematika Thales, 7(1). https://doi.org/10.22146/jmt.108835
Triningsih. (2025). Analisis Sentimen Terhadap Program Makan Bergizi Gratis Menggunakan Algoritma Machine Learning Pada Sosial Media X. https://doi.org/10.47065/bits.v6i4.6534
Wibowo, Fatchan, & Supriyanto. (2026). Analisis Sentimen Multikelas Program Makan Bergizi Gratis di Media Sosial X Menggunakan VaderSentiment dan SVM Berbasis Oversampling SMOTE. https://doi.org/10.47065/bulletinds.v5i3.10323
Wulandari, Musyafa, & Wiharjo. (2026). Analisis Sentimen Masyarakat Media Sosial Twitter Terhadap Program Makan Bergizi Gratis Menggunakan IndoBERT dan DistilBERT. https://doi.org/10.47970/siskom-kb.v9i3.904
Zimbra, D., Abbasi, A., Zeng, D., & Chen, H. (2018). The state-of-the-art in Twitter sentiment analysis: A review and benchmark evaluation. ACM Transactions on Management Information Systems, 9(2), 5. https://doi.org/10.1145/3185045
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Indri Anjar Kartika Sari, Chess Suratnoaji, Agus Widiyarta (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.






















