Sentiment Analysis of the Free Nutritious Meals Program using Linear Learner and Adaboost Algorithms
DOI:
https://doi.org/10.32832/astonjadro.v15i4.22959Keywords:
sentiment analysis, free nutritious meal program, logistic regression, adaboost, machine learning.Abstract
The government initiative through the Free Nutritious Meals Program is designed to intervene in the nutritional quality of the community, especially for students in schools. Given that this policy has sparked widespread discussion on social media platforms, this study aims to map public opinion trends through sentiment analysis. The main focus of this study is to apply a Logistic Regression-based Linear Learner algorithm integrated with the AdaBoost ensemble learning technique to classify text data. Primary data was collected from the Threads platform, which was then processed through a series of systematic stages including text preprocessing, feature extraction, and separation between training and test data for positive and negative sentiment categories. In this experiment, Logistic Regression acts as the base classifier, while AdaBoost is used as a strategy to optimize classification accuracy. Model performance evaluation was conducted comprehensively using accuracy, precision, recall, and F1-score parameters. The research findings confirm that adding the AdaBoost method to the Logistic Regression framework significantly improves classification quality compared to when the algorithm is used alone. The developed model was proven to produce higher metrics and a more stable distribution of values. Therefore, the synergy between Logistic Regression and AdaBoost is a reliable approach to evaluate public perception of public policy implementation.
References
[1] S. Ayu, F. Wahyuni, and Z. Risal, “Al-Kharaj : Jurnal Ekonomi , Keuangan & Bisnis Syariah Persiapan Menuju Indonesia Emas 2045 : Analisis Efektifitas Al-Kharaj : Jurnal Ekonomi , Keuangan & Bisnis Syariah,” vol. 8, no. 1, pp. 538–546, 2026, doi: 10.47467/alkharaj.v8i1.10895.
[2] A. Albaburrahim, A. P. A. Putikadyanto, A. N. Efendi, M. A. Alatas, S. Romadhon, and L. R. Wachidah, “Program Makan Bergizi Gratis: Analisis Kritis Transformasi Pendidikan Indonesia Menuju Generasi Emas 2045,” Entita J. Pendidik. Ilmu Pengetah. Sos. dan Ilmu-Ilmu Sos., pp. 767–780, May 2025, doi: 10.19105/ejpis.v1i.19191.
[3] R. Qomarrullah, S. Suratni, L. Wulandari S, and M. Sawir, “Dampak Jangka Panjang Program Makan Bergizi Gratis terhadap Kesehatan dan Keberlanjutan Pendidikan,” Indones. J. Intellect. Publ., vol. 5, no. 2, pp. 130–137, Mar. 2025, doi: 10.51577/ijipublication.v5i2.660.
[4] W. T. Aji, “Makan Bergizi Gratis di Era Prabowo-Gibran: Solusi untuk Rakyat atau Beban Baru?,” NAAFI J. Ilm. Mhs., vol. 1, no. 3, pp. 215–226, 2025.
[5] G. Rota, “Threads by Meta: Redefining Social Media Dynamics, Challenges, and Unique Features. Professionals’ Opinions and Social Media Users’ Perceptions,” 2024, Universidade NOVA de Lisboa (Portugal).
[6] F. Vasilopoulos, “Hanging by a Thread: Meta’s New Platform, Threads, Sheds Light on the Slow Unraveling of Individual Privacy,” UIC L. Rev., vol. 58, p. 473, 2024.
[7] M. W. Arif, “Analisis Sentimen Kebijakan Makan Bergizi Gratis di Media Sosial Menggunakan Natural Language Processing Berbasis Python TextBlob di Indonesia Teknik Informatika , Universitas Ngudi Waluyo , Indonesia Sentiment Analysis of Free Nutritious Meal Policy on S,” vol. 5, no. 9, pp. 2463–2471, 2025, doi: 10.52436/1.JPTI.931.
[8] U. Arfan and E. Badii, “Sentiment Analysis of Papuan Public Perceptions Toward the Free Nutritional Meal Program in Indonesia Analisis Sentimen Masyarakat Papua Terhadap Program Makan Gizi Gratis di Indonesia,” vol. 5, no. October, pp. 1538–1546, 2025, doi: 10.57152/malcom.v5i4.2087.
[9] N. N. Aprianti et al., “Public Sentiment Analysis of the Free Nutritious Meals Program ( MBG ) on Social Media X Using the Naive Bayes Method,” vol. 9, no. 6, pp. 3929–3936, 2025.
[10] Nursakina, F. Wajidi, and M. R. Rasyid, “Evaluasi algoritma KNN dan Naive Bayes untuk analisis sentimen kebijakan program makan bergizi gratis,” vol. 7, no. 2, pp. 83–97, 2025, doi: 10.37905/jji.v1i2.34418.
[11] K. Y. Pratama, S. Achmadi, and K. A. Sari, “Analisis Sentimen Terhadap Makan Bergizi Gratis Pada Sosial Media X Menggunakan Metode Decicion Tree Dengan Pembanding Naive Bayes,” vol. 9, no. 6, pp. 11061–11067, 2025.
[12] E. Mulyani, F. P. B. Muhamad, and K. A. Cahyanto, “Pengaruh N-Gram terhadap Klasifikasi Buku menggunakan Ekstraksi dan Seleksi Fitur pada Multinomial Naïve Bayes,” J. Media Inform. Budidarma, vol. 5, no. 1, p. 264, 2021, doi: 10.30865/mib.v5i1.2672.
[13] A. D. M. Putri, N. Sulistianingsih, and R. Rismayati, “Pengaruh Teknik Representasi Teks Bag-of-Words dan TF-IDF terhadap Akurasi Klasifikasi Sentimen Teks Multi-Domain,” vol. 7, no. 4, pp. 675–688, 2025.
[14] M. Erkamim, A. M. Tanniewa, and I. Ap, “Analisis Perbandingan Metode AdaBoost , Gradient Boosting , dan XGBoost Untuk Kalsifikasi Status Gizi Pada Balita,” vol. 6, no. 3, pp. 1799–1807, 2024, doi: 10.47065/bits.v6i3.5717.
[15] A. Nanda and H. W. Perdana, “Perbandingan Efektivitas Random Forest , SVM , dan Logistic Regression dalam Deteksi Intrusi Jaringan,” vol. 12, no. 2, pp. 129–139, 2025.
[16] S. K. Wardani and Y. A. Sari, “Analisis Sentimen menggunakan Metode Naïve Bayes Classifier terhadap Review Produk Perawatan Kulit Wajah menggunakan Seleksi Fitur N-gram dan Document Frequency Thresholding,” vol. 5, no. 12, pp. 5582–5590, 2021.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 ASTONJADRO
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Paper submitted to ASTONJADRO is the sole property of the Astonjadro Journal. Unless the author withdraws the paper because he does not want to be published in this journal. The publication rights are in the journal Astonjadro.ASTONJADRO
LICENSE
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at http://ejournal.uika-bogor.ac.id/index.php/ASTONJADRO
