Sentiment Analysis on Free Lunch & Milk Program Using Naive Bayes Algorithm
Abstract
The utilization of social media platforms like Twitter has become crucial for the public to voice opinions regarding political programs, including the Free Lunch and Milk Program advocated by Presidential Candidate Pair number 02, Prabowo-Gibran, in the 2024 Presidential Election. This research employs the Naive Bayes classification method with the assistance of the RapidMiner application to analyze public sentiment towards the program. Out of the 785 Twitter data examined, approximately 81.7% displayed negative sentiment, while 6.6% were neutral, and 11.7% exhibited positive sentiment. Despite the prevalence of negative sentiment, there was also support for the program. Model evaluation utilizing 10-fold cross-validation, alongside SMOTEUP sampling and TF-IDF implementation, revealed an accuracy of 92.96%, recall of 85.30%, and precision of 94.57%. These results indicate that the model performs well in classifying sentiment from the test data.
Downloads
References
D. Wiryany, S. Natasha, and R. Kurniawan, “PERKEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIKASI TERHADAP PERUBAHAN SISTEM KOMUNIKASI INDONESIA,” Jurnal Nomosleca, vol. 8, no. 2, pp. 242–252, 2022.
“Visi, Misi dan Program Calon Presiden dan Wakil Presiden 2024-2029 H. Prabowo Subianto, Gibran Rakabuming Raka,” medcom.id. Accessed: May 18, 2024. [Online]. Available: https://va.medcom.id/2023/pemilu/others/PRABOWOGIBRAN_VISI_MISI.pdf
V. E. Togatorop, L. Rahayuwati, and R. D. Susanti, “Predictor of Stunting Among Children 0-24 Months Old in Indonesia: A Scoping Review,” Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini, vol. 7, no. 5, pp. 5654–5674, 2023, doi: 10.31004/obsesi.v7i5.5222.
N. Aurora Prameswari et al., “Public Search Interest in Stunting Interventions as an Effort to Reduce the Incidence of Stunting in Indonesia during 2018-2022: A Google Trends Analysis,” Amerta Nutrition, vol. 7, no. 3SP, pp. 41–49, 2023, doi: 10.20473/amnt.v7i3SP.2023.41- 49.
R. N. Chatarine, “TKN: Dana Program Makan Siang Gratis Rp 450 Triliun, Tak Gunakan Dana Bansos,” nasional.kompas.com. Accessed: May 18, 2024. [Online]. Available: https://nasional.kompas.com/read/2023/12/20/19132411/tkn-dana-program-makan-siang-gratis-rp-450-triliun-tak-gunakan-dana-bansos
R. Mulyana, H. Pramadya, and N. R. Vindiazhari, “Pelatihan Literasi Digital Lembaga Untuk Lanjut Usia Indonesia (LLI) Kota Bandung Digital Literacy Training For Lembaga Lanjut Usia (LLI) Bandung City,” Solusi Bersama : Jurnal Pengabdian dan Kesejahteraan Masyarakat, vol. 1, no. 2, pp. 01–07, 2024.
A. Kartino, M. K. Anam, Rahmaddeni, and Junadhi, “Analisis Akun Twitter Berpengaruh terkait Covid-19 menggunakan Social Network Analysis,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 4, pp. 697–704, Aug. 2021, doi: 10.29207/resti.v5i4.3160.
D. Setiyawati and N. Cahyono, “Analisa Sentimen Pengguna Sosial Media Twitter Terhadap Perokok di Indonesia,” Indonesian Journal of Computer Science, vol. 12, no. 1, pp. 262–272, 2023.
A. Nugroho and Y. Religia, “Analisis Optimasi Algoritma Klasifikasi Naive Bayes menggunakan Genetic Algorithm dan Bagging,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 3, pp. 504–510, Jun. 2021, doi: 10.29207/resti.v5i3.3067.
S. K. P. Loka and A. Marsal, “Perbandingan Algoritma K-Nearest Neighbor dan Naïve Bayes Classifier Untuk Klasifikasi Status Gizi Pada Balita,” MALCOM: Indonesian Journal of Machine Learning and Computer Science, vol. 3, no. 1, pp. 8–14, 2023.
E. Febriyani and H. Februariyanti, “Analisis Sentimen Terhadap Program Kampus Merdeka Menggunakan Algoritma Naive Bayes Classifier Di Twitter,” Jurnal TEKNO KOMPAK, vol. 17, no. 1, pp. 25–38, 2023.
J. Florensius Sianipar, Y. R. Ramadhan, and I. Jaelani, “Analisis Sentimen Pembangunan Kereta Cepat Jakarta-Bandung di Media Sosial Twitter Menggunakan Metode Naive Bayes,” KLIK: KAJIAN ILMIAH INFORMATIKA DAN KOMPUTER, vol. 4, no. 1, pp. 360–367, 2023, doi: 10.30865/klik.v4i1.1033.
M. I. Ghozali, W. H. Sugiharto, and A. F. Iskandar, “KLIK: Kajian Ilmiah Informatika dan Komputer Analisis Sentimen Pinjaman Online Di Media Sosial Twitter Menggunakan Metode Naive Bayes,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 3, no. 6, pp. 1340–1348, 2023, doi: 10.30865/klik.v3i6.936.
P. Paramita and A. Ibrahim, “ANALISIS SENTIMEN TERHADAP PENGGUNA QRIS (QUICK RESPOND CODE INDONESIAN STANDART) PADA TWITTER MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER,” JOISIE Journal Of Information System And Informatics Engineering, vol. 7, no. 1, pp. 1–6, 2023, [Online]. Available: https://t.co/lJemg7TbKb
Sulindawaty, E. Laia, and M. Yamin, “Penerapan Algoritma Naïve Bayes dalam Menganalisis Sentimen pada Review Pengguna E-Commerce,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 4, no. 1, pp. 305–316, 2023, doi: 10.30865/klik.v4i1.1186.
R. A. Firsttama, A. A. Arifiyanti, and D. S. Y. Kartika, “Analisis Sentimen Komentar Youtube Konferensi Tingkat Tinggi G20 Menggunakan Metode Naive Bayes,” Jurnal Teknologi Dan Sistem Informasi Bisnis, vol. 6, no. 2, pp. 282–285, Apr. 2024, doi: 10.47233/jteksis.v6i2.1263.
W. Gunawan, R. A. Wiradiputra, A. P. Sari, D. Prayama, and E. R. Nainggolan, “Prediction of Cross-Platform and Native Apps Technology Opportunities for Beginner Developers Using C 4.5 and Naïve Bayes Algorithms,” JOIV : International Journal on Informatics Visualization, vol. 7, no. 4, pp. 2145–2153, Dec. 2023, doi: http://dx.doi.org/10.30630/joiv.7.4.01514.
N. T. S. Saptadi, P. Chyan, and J. M. Leda, “Analysis of Supermarket Product Purchase Transactions With the Association Data Mining Method,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 7, no. 3, pp. 618–627, Jun. 2023, doi: 10.29207/resti.v7i3.4844.
A. Algiffary and T. Sutabri, “Implementasi Machine Learning dengan Algoritma Naive Bayes Terhadap Sistem Informasi Pelayanan Pemberkasan Kepegawaian di BKPSDM Kota Palembang,” Indonesian Journal of Computer Science, vol. 12, no. 3, pp. 1272–1281, 2023.
B. Bayu Baskoro, I. Susanto, and S. Khomsah, “Analisis Sentimen Pelanggan Hotel di Purwokerto Menggunakan Metode Random Forest dan TF-IDF (Studi Kasus: Ulasan Pelanggan Pada Situs TRIPADVISOR),” Journal of Informatics, Information System, Software Engineering and Applications, vol. 3, no. 2, pp. 21–029, 2021, doi: 10.20895/INISTA.V3I2.
M. Hayaty, S. Muthmainah, and S. M. Ghufran, “Random and Synthetic Over-Sampling Approach to Resolve Data Imbalance in Classification,” International Journal of Artificial Intelligence Research, vol. 4, no. 2, pp. 86–94, Dec. 2020, doi: 10.29099/ijair.v4i2.152.
R. Aryanti, T. Misriati, and R. Hidayat, “Klasifikasi Risiko Kesehatan Ibu Hamil Menggunakan Random Oversampling Untuk Mengatasi Ketidakseimbangan Data,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 3, no. 5, pp. 409–416, Apr. 2023, [Online]. Available: https://djournals.com/klik
C. H. Yutika, Adiwijaya, and S. Al Faraby, “Analisis Sentimen Berbasis Aspek pada Review Female Daily Menggunakan TF-IDF dan Naïve Bayes,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 5, no. 2, pp. 422–430, Apr. 2021, doi: 10.30865/mib.v5i2.2845.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under an Attribution 4.0 International (CC BY 4.0) that allows others to share — copy and redistribute the material in any medium or format and adapt — remix, transform, and build upon the material for any purpose, even commercially with an acknowledgment of the work's authorship and initial publication in this journal.
