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Ari Wedhasmara
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Social Sciences Other

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Sentiment Analysis of Food Poisoning Incidents in Indonesia's Free Nutritious Meal Program Using TF-IDF and SVM Muhammad Lucky Hermanto; Ari Wedhasmara; Ken Ditha Tania; Allsela Meiriza
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 3 (2026): DECEMBER 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i3.7809

Abstract

Food poisoning incidents associated with the Free Nutritious Meal Program (MBG) have triggered significant public reactions on the social media platform X/Twitter. This study identified and classified public sentiment regarding food poisoning occurrences in the MBG program by applying a Support Vector Machine (SVM) classification framework. Data were crawled from X/Twitter via Tweet Harvest using keywords related to MBG food poisoning incidents between January 2025 and June 2026. A total of 6,929 posts were collected, and 6,902 Indonesian-language records were retained after duplicate removal. The analytical workflow comprised data selection, automated sentiment labeling with IndoBERTweet, text preprocessing, Term Frequency-Inverse Document Frequency (TF-IDF) feature weighting, and classification using the SVM algorithm. Model performance was evaluated through a confusion matrix using accuracy, precision, recall, and F1-score metrics. Based on an evaluation of 1,989 testing records, the SVM model achieved an overall accuracy of 76.42%, exhibiting its strongest performance in the negative sentiment class. However, positive sentiment recorded a low recall of 26.03%, reflecting the difficulty of detecting the minority class. Sentiment distribution analysis revealed that negative sentiment dominated public discourse at 63.78%, followed by neutral sentiment at 29.05% and positive sentiment at 7.17%. These findings indicate that public perceptions of food poisoning incidents in the MBG program were overwhelmingly negative, underscoring critical concerns regarding food safety and program oversight. Beyond contributing to machine learning-based social media analytics, this study provides actionable insights for policymakers to evaluate service delivery and reinforce food safety standards in the MBG program.
Co-Authors Abdiansah, Abdiansah Ahmad Rafid Rizqullah Ahmad Rifai Ali Bardadi Ali Ibrahim Ali Ibrahim (SCOPUS ID: 57203129436) Aliyah Khofifah Allsela Meiriza, Allsela Alvi Syahrini Utami Alzena Aisha Shakira Ananda Khoirunnisa Annisa Tri Ning Tyas Apriansyah Putra Apriansyah Putra Apriansyah Putra Apriansyah Putra Arba'i, Sultan Ardina Ariani Ariyani, Ishlah Putri Ariyanti, Putri Charolin, Nurhaliza Cici Elna Sari Dafa Al Faris Anwar Dedy Kurniawan Dinda Lestarini Dinna Yunika Hardiyanti Dwi Rosa Indah Elly Kurniati Elna Sari, Cici Faris, Haninda Ammar Fathoni - Fauzan, Muhammad Fairuz Fitri, Shofiyah Gusti Barata Hardini Novianty Iin Seprina Inayah, Anna Fadilla Inka Marissa Jambak, Muhammad Ihsan Jasmo ari wibowo Kanda Januar Miraswan Keisha Angelina Tompunu Ken Dhita Tania Ken Ditha Tania Ken Ditha Tania M. Rudi Sanjaya Mgs Afriyan Firdaus Miftahul Falah Mira Afrina Mira Afrina Muhammad Fakhri Nadrota Acta Muhammad Farhan Muhammad Hafiz Al Zaky Muhammad Lucky Hermanto Mukhlis Febriady Nadia Anggraini Naretha Kawadha Pasemah Gumay Novi Yusliani Oktadini, Nabila Rizky Pacu Putra Putri Ariyanti Putri Eka Sevtiyuni Putri Eka Sevtyuni Putri, Amelia Rizki Rahmat Izwan Heroza Rahmayuni, Septa Raihana Nabilatulrahmah Rani Mardiah Reina Salsa Kinanty Revi Amelia Dwifa Futri Riska Yunita Rizka Dhini Kurnia Rizka Dhini Kurnia Rizka Dhini Kurnia Rusdi Efendi Sevtiyuni, Putri Eka Sultan Arba'i Umar Rahman Zidan Wulan Dari, Atikah