Application of Naive Bayes Classifier Method to Analyze Social Media User Sentiment Towards the Presidential Election Phase

Main Article Content

Firdaus Yuni Dharta
Ardhana Januar Mahardhani
Sitti Rachmawati Yahya
Andika Dirsa
Elvira M. Usulu

Abstract

This research aims to analyze the sentiment of social media users towards the election. The author collected data in this research through a literature study and observation. The author uses a classification method with the Naïve Bayes Classifier Algorithm and Support Vector Machine to analyze sentiment results. Next, this research extracts word assessment features using TextBlob, which changes text into positive or negative classes. Based on the research results, after going through the text preprocessing stage of more than 15,000 tweets, 11,000 clean tweets were obtained, which were then labelled using the text blob library in Python. The labelling results show that 4,000 tweets are positive, and the rest are harmful, indicating that most social media users' sentiment towards the election is positive. Words that often appear in the positive class express support and confidence in implementing elections that are considered honest and fair. On the other hand, words in the negative class reflect negative sentiment towards implementing elections, which are considered unsuccessful and time-consuming. The Naïve Bayes method provides accuracy, precision, and recall values of 85%, 80%, and 75%. In the Support Vector Machine method, testing is carried out with three kernels (linear, RBF, and poly), where the poly kernel with the best parameter values C is ten and degree is 1 produces the highest accuracy, precision, and recall of 90%, 90%, and 85%, respectively.

Article Details

How to Cite
Dharta, F. Y., Januar Mahardhani, A., Rachmawati Yahya, S., Dirsa, A., & M. Usulu, E. (2024). Application of Naive Bayes Classifier Method to Analyze Social Media User Sentiment Towards the Presidential Election Phase. Jurnal Informasi Dan Teknologi, 6(1), 176-181. https://doi.org/10.60083/jidt.v6i1.494
Section
Articles

References

[1] Aulia, G. N., & Patriya, E, "Implementation of Lexicon Based and Naive Bayes in Twitter User Sentiment Analysis on the 2019 Presidential Election Topic," Jurnal Ilmiah Informatika Komputer, vol. 24, no. 2, pp. 140–153, 2019.
[2] Mahardhani, A. J. (2023). The Role of Public Policy in Fostering Technological Innovation and Sustainability. Journal of Contemporary Administration and Management (ADMAN), 1(2), 47-53.
[3] Tannady, H., Dewi, C. S., & Gilbert. (2024). Exploring Role of Technology Performance Expectancy, Application Effort Expectancy, Perceived Risk and Perceived Cost On Digital Behavioral Intention of GoFood Users. Jurnal Informasi Dan Teknologi, 6(1), 80-85. https://doi.org/10.60083/jidt.v6i1.477
[4] Madyatmadja, E. D., Marvell, M., Andry, J. F., Tannady, H., & Chakir, A. (2021, August). Implementation of big data in hospital using cluster analytics. In 2021 International Conference on Information Management and Technology (ICIMTech) (Vol. 1, pp. 496-500). IEEE.
[5] Destari, D., Tannady, H., Zainal, A. G., Nurjanah, S., & Renwarin, J. M. (2021). The Improvement of Employee's Performance in Plastic Ore Industry: Mediating Role of Work Motivation. Turkish Online Journal of Qualitative Inquiry, 12(7).
[6] Chaudhry, H. N., Javed, Y., Kulsoom, F., Mehmood, Z., Khan, Z. I., Shoaib, U., & Janjua, S. H, "Sentiment analysis of before and after elections: Twitter data of Election 2020," Electronics (Switzerland), vol. 10, no. 17, pp. 1–26, 2021.
[7] Diawati, P., Gadzali, S. S., Mahardhani, A. J., Irawan, B., & Ausat, A. M. A. (2023). Analyzing the Dynamics of Human Innovation in Administration. Jurnal Ekonomi, 12(02), 537-540.
[8] Parlika, R., Pradika, S. I., Hakim, A. M., & N M, K. R, “Twitter Sentiment Analysis of Bitcoin and Cryptocurrencies Based on Python Textblob,” Jurnal Ilmiah Teknologi Informasi Dan Robotika, vol. 2, no. 2, pp. 33–37, 2020, https://doi.org/10.33005/jifti.v2i2.22
[9] Octiva, C. S., Israkwaty, Nuryanto, U. W., Eldo, H., & Tahir, A. (2024). Application of Holt-Winter Exponential Smoothing Method to Design a Drug Inventory Prediction Application in Private Health Units. Jurnal Informasi Dan Teknologi, 6(1), 1-6. https://doi.org/10.60083/jidt.v6i1.464
[10] Hendy, T., Resdiansyah, R., Johanes, F. A., & Rustono, F. M. (2020). Exploring the role of ICT readiness and information sharing on supply chain performance in coronavirus disruptions. Technol. Rep. Kansai Univ, 62, 2581-2588.
[11] Pintoko, B. M., & L., K. M, “Sentiment Analysis of Online Transportation Services on Twitter Using the Naive Bayes Classifier Method,” E-Proceeding of Engineering, vol. 5, no. 3, pp. 8121–8130, 2018.
[12] Gunawan, F. E., Suyoto, Y. T., & Tannady, H. (2020). Factors affecting job performance of hospital nurses in capital city of Indonesia: Mediating role of organizational citizenship behavior. Test Engineering and Management, 83, 22513-22524.
[13] Rokhman, K. A., Berlilana, B., & Arsi, P, "Comparison of Support Vector Machine and Decision Tree Methods for Sentiment Analysis Review Comments on Online Transportation Applications," Journal of Information System Management (JOISM), vol. 3, no. 1, pp. 1–7, 2021.
[14] Sutrisno, S., Tannady, H., Ekowati, D., MBP, R. L., & Mardani, P. B. (2022). Analisis Peran Kualitas Produk Dan Visual Identity Terhadap Purchase Intention Produk Teh Dalam Kemasan. Management Studies and Entrepreneurship Journal (MSEJ), 3(6), 4129-4138.
[15] Andry, J. F., Tannady, H., & Nurprihatin, F. (2020, March). Eliciting requirements of order fulfilment in a company. In IOP Conference Series: Materials Science and Engineering (Vol. 771, No. 1, p. 012023). IOP Publishing.
[16] Solehati, A., Mustafa, F., Hendrayani, E., Setyawati, K., Kusnadi, I. H., Suyoto, Y. T., & Tannady, H. (2022). Analisis Pengaruh Store Atmosphere dan Service Quality Terhadap Brand Preference (Studi Kasus Pelanggan Gerai Ritel Kopi di DKI Jakarta). Jurnal Kewarganegaraan, 6(2), 5146-5147.
[17] Basrah S & Samsul I, “The Influence of Product Quality and Service Quality on Consumer Satisfaction,” Jurnal Riset Manajemen Sains Indonesia (JRMSI), vol.3, no.1, 2022.
[18] D. Abdullah, “Perancangan Sistem Informasi Pelayanan Kapal,” J. Ilm. Teknol. Inf. Terap., 2015.
[19] Hasanun, D. Abdullah, and M. Daud, “Pengembangan Sistem E-Learning Politeknik Negeri Lhokseumawe dengan Model Vark ”, jidt, vol. 5, no. 4, pp. 222-228, Dec. 2023.
[20] A. Faridhatul Ulva, D. Abdullah, Masriadi, Nurhasanah, N. Alimul Haq, and B. Ulumul Haq, “AROS(AgRO-Smart) : Smart City Pertanian dengan Track and Trace GPS berbasis Mobile”, jidt, vol. 5, no. 4, pp. 78-91, Nov. 2023.
[21] D. . K. Pramudito, A. . Titin Sumarni, E. . Diah Astuti, B. . Aditi, and Magdalena, "The Influence of User Trust and Experience On User Satisfaction Of E-Commerce Applications During Transactions in Mini Markets Using Delon and McLean Method", jsisfotek, vol. 5, no. 4, pp. 1–7, Oct. 2023.
[22] S. Budi Utomo, J. P. Nugraha, E. Sri wahyuningsih, R. . Indrapraja, and F. A. . Binsar Kristian Panjaitan, “Analysis of The Effectiveness of Integrated Digital Marketing Communication Strategies in Building MSMEs Brand Awareness Through Social Media”, jsisfotek, vol. 5, no. 4, pp. 8–13, Oct. 2023.

Most read articles by the same author(s)