Comparison of SVM and Naive Bayes in MBG Sentiment Analysis on TikTok and Instagram Platforms
Comparison of SVM and Naive Bayes in MBG Sentiment Analysis on TikTok and Instagram Platforms
DOI:
https://doi.org/10.33998/jakakom.2026.6.1.2750Keywords:
Sentiment Analysis, Support Vector Machine, Naive Bayes, Sosial Media, Tiktok, Instagram, MBG, Text Mining, Machine LearningAbstract
The rapid growth of social media has made platforms such as TikTok and Instagram primary channels for the public to express opinions on various public issues, including the Free Nutritious Meal Program (MBG). The large volume of user-generated comments makes manual analysis inefficient, thereby requiring sentiment analysis approaches based on machine learning. This study aims to analyze public sentiment toward the MBG program and to compare the performance of Support Vector Machine (SVM) and Naive Bayes (NB) methods in classifying sentiments into positive, negative, and neutral categories. The dataset consists of 6,001 comments collected from TikTok and Instagram through a web scraping process using Apify and Python. The research stages include data collection, text preprocessing, feature extraction, model training, and evaluation using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The results of this study are expected to provide a comparison of the performance of SVM and Naive Bayes algorithms as well as an overview of public opinion trends regarding the MBG program on social media.
Downloads
References
G. C. Hermawan And D. F. Suyatno, “Analisis Kepuasan Pelanggan Terhadap Layanan Aplikasi Klik Indomaret Menggunakan Metode End User Computing Satisfaction (Eucs) Dan Delone And Mclean,” Progr. Stud. Sist. Inf. Fak. Sains Dan Teknol. Univ. Islam Negeri Syarif Hidayatullah, Vol. 4, No. 1, Pp. 88–100, 2023,doi: https://doi.org/10.26740/jeisbi.v4i3.54230
N. P. Husain, S. Sukirman, And S. Sajiah, “Analisis Sentimen Ulasan Pengguna TikTok Pada Google Play Store Berbasis Tf-Idf Dan Support Vector Machine,” J. Syst. Comput. Eng., Vol. 5, No. 1, Pp. 91–102, 2024, doi: https://doi.org/10.61628/jsce.v5i1.1105.
N. Muhamad, “Ini Media Sosial Terpopuler Di Dunia Pada Pertengahan 2025.” [Online]. Available: https://databoks.katadata.co.id/media-sosial/statistik/6891de083c9b7/indonesia-masuk-20-negara-paling-sering-akses-media-sosial-kuartal-i-2025.
N. Apriliani Et Al., “Analisis Sentimen Review Penggunaan TikTok Melalui Pendekatan Algoritma Naïve Bayes,” Vol. 7, No. 6, Pp. 3725–3731, 2023.
M. A. Rizaty, “Kumpulan Data Seputar TikTok Di Dunia Dan Indonesia Hingga April 2025.” [Online]. Available: https://dataindonesia.id/internet/detail/laporan-kumpulan-data-seputar-tiktok-di-dunia-dan-indonesia-hingga-april-2025.
N. Cahyono, S. Informatika, And U. A. Yogyakarta, “Analisis Sentimen Komentar Instagram Pada Program Kampus,” Vol. 8, No. 2, Pp. 2372–2381, 2024.
M. A. Rizaty, “Negara Pengguna Instagram Terbesar.” [Online]. Available: https://dataindonesia.id/internet/detail/jajaran-negara-pengguna-instagram-terbanyak-pada-oktober-2025-indonesia-keempat.
K. Andreas Et Al., “Tinjauan Kritis Tentang Program Makan Bergizi Gratis Terhadap Produktivitas Belajar Siswa,” Vol. 2, 2025. doi : https://share.google/zrIMkjFxJPZDY2bCO
M. A. Rojabi, Mitra Bgn: Syarat, Cara Daftar Online, Dan Kunci Lolos Verifikasi Program Makan Bergizi Gratis. Yogyakarta: Penerbit Andi, 2024.j
L. Nursinggah, T. Mufizar, And U. Perjuangan, “Analisis Sentimen Pengguna Aplikasi X Terhadap Program Makan Siang Gratis,” Vol. 12, No. 3, 2024.
B. Rahmatullah, S. A. Saputra, P. Budiono, And D. P. Wigandi, “Sentimen Analisis Makan Bergizi Gratis Menggunakan Algoritma Naive Bayes,” J. Inf. Technol., Vol. 5, No. 1, 2025, doi: https://doi.org/10.46229/jifotech.v5i1.978.
A. Sitanggang, Y. Umaidah, R. I. Adam, U. S. Karawang, And T. Timur, “Analisis Sentimen Masyarakat Terhadap Program Makan Siang Gratis Pada Media,” Vol. 12, No. 3, 2024.
N. Putu Alya Noviyanti Et Al., “Penerapan Multinomial Naïve Bayes Dan Chi-Square Pada Analisis Sentimen Makan Bergizi Gratis,” Jnatia, Vol. 3, No. 4, Pp. 785–794, 2025.
M. M. Laia Et Al., “Analisis Sentimen Program Makan Gratis Pada Platform X Algoritma Naïve Bayes Menggunakan,” 2025.
A. Ardiansyah, Suleman, E. A. Pratama, And N. I. Fadlilah, “Analisis Sentimen Pengguna Terhadap Aplikasi Chatgpt Di Google Play Store: Penerapan Algoritma Support Vector Machine,” J. Tek. Inform. Dan Sist. Inf., Vol. 11, No. 2, Pp. 247–254, 2024.
Sukri And D. Arisandi, “Jurnal Resti,” Resti, Vol. 1, No. 1, Pp. 19–25, 2020.
A. Pebdika, R. Herdiana, And D. Solihudin, “Klasifikasi Menggunakan Metode Naive Bayes Untuk Menentukan Calon Penerima Pip,” Jati (Jurnal Mhs. Tek. Inform., Vol. 7, No. 1, Pp. 452–458, 2023, doi: https://doi.org/10.36040/jati.v7i1.6303.
M. C. Ari Muzakir, S.Kom., M. . Prof.Dr.Kusworo Adi, S.Si., And M. K. Dr.Retno Kusumanigrum, S.Si., Penerapan Konsep Machine Learning & Deep Learning. 2024.
J. Informatika And S. Informasi, “Informasi (Jurnal Informatika Dan Sistem Informasi) Volume 12 No.1 / Mei/ 2020,” Vol. 12, No. 1, Pp. 67–80, 2020.
