The Public Sentiment Analysis on the 2024 Presidential Election Using Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) On Social Media Data
Keywords:
2024 Presidential Election, Sentiment Anaysis, Naive Bayes Classifier, Support Vector Mschine, Youtube, Social MediaAbstract
This study aims to evaluate the effectiveness of the Naive Bayes Classifier (NBC) and Support Vector Machine (SVM) in analyzing public sentiment from YouTube comments related to the 2024 Indonesian Presidential Election. A total of 1,800 comments, collected from November 2023 to March 2024, were analyzed to test these models. The results show that SVM, with the highest accuracy of 76.33% and precision and F1-Score of 75.29% and 72.67% on the 10% test data, outperformed NBC, which recorded a highest accuracy of 72.19% under similar conditions. These findings highlight the importance of using more sophisticated methods in sentiment analysis to understand the complex and diverse dynamics of public opinion. This study provides valuable insights for stakeholders in developing effective communication strategies and offers a foundation for advancing sentiment analysis methodologies in political contexts.
References
Alexander, Nyongki, Radja Bria, and Arita Witanti. 2023. ANALISIS SENTIMEN MASYARAKAT INDONESIA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE TENTANG PILPRES 2024. Vol. 7.
Alfonso, Michael, and Dionisia Bhisetya Rarasati. n.d. “JISA (Jurnal Informatika Dan Sains) Sentiment Analysis of 2024 Presidential Candidates Election Using SVM Algorithm.”
Anam, M. Khairul, Triyani Arita Fitri, Agustin Agustin, Lusiana Lusiana, Muhammad Bambang Firdaus, and Agus Tri Nurhuda. 2023. “Sentiment Analysis for Online Learning Using The Lexicon-Based Method and The Support Vector Machine Algorithm.” ILKOM Jurnal Ilmiah 15(2):290–302. doi: 10.33096/ilkom.v15i2.1590.290-302.
Ansori, Yusuf, and Khadijah Fahmi Hayati Holle. 2022. “Perbandingan Metode Machine Learning Dalam Analisis Sentimen Twitter.” Jurnal Sistem Dan Teknologi Informasi (JustIN) 10(4):429. doi: 10.26418/justin.v10i4.51784.
Azzawagama Firdaus, Asno, Anton Yudhana, and Imam Riadi. 2024. “Prediction of Indonesian Presidential Election Results Using Sentiment Analysis with Naïve Bayes Method.” doi: 10.30865/mib.v8i1.7007.
Bustomi, Yosep, Anwar Nugraha, Christina Juliane, and Sri Rahayu. 2023. “Data Mining Selection of Prospective Government Employees with Employment Agreements Using Naive Bayes Classifier.” Sinkron 8(1):1–8. doi: 10.33395/sinkron.v8i1.11968.
Christian, Yefta, Tony Wibowo, and Mercy Lyawati. 2024. “Sentiment Analysis by Using Naïve Bayes Classification and Support Vector Machine, Study Case Sea Bank.” Sinkron 9(1):258–75. doi: 10.33395/sinkron.v9i1.13141.
Damayanti, Lisyana, and Kemas Muslim Lhaksmana. 2024. “Sentiment Analysis of the 2024 Indonesia Presidential Election on Twitter.” Jurnal Dan Penelitian Teknik Informatika 8(2). doi: 10.33395/v8i2.13379.
Fadlila Nurwanda, Winita Sulandari, Yuliana Susanti, and Zakya Reyhana. 2023. “Comparative Analysis Of Performance Levels Of Svm And Naïve Bayes Algorithm For Lifestyle Classification On Twitter Social Media.” INTERNATIONAL CONFERENCE ON DIGITAL ADVANCE TOURISM, MANAGEMENT AND TECHNOLOGY 1(1):215–30. doi: 10.56910/ictmt.v1i1.65.
Firdaus, Asno Azzawagama, Anton Yudhana, Imam Riadi, and Mahsun. 2024. “Indonesian Presidential Election Sentiment: Dataset of Response Public before 2024.” Data in Brief 52. doi: 10.1016/j.dib.2023.109993.
Geni, Lenggo, Evi Yulianti, and Dana Indra Sensuse. 2023. “Sentiment Analysis of Tweets Before the 2024 Elections in Indonesia Using IndoBERT Language Models.” Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika (JITEKI) 9(3):746–57. doi: 10.26555/jiteki.v9i3.26490.
Guru, Peran, Dalam Mengembangk, An Karakter, Peserta Didik Smkn, Jakarta Timur, Maryam Sulaeman, Muhammad Bachrun’, Ulum Romadhoni, Frencis Matheos Sarimole, and Wahyu Septian. 2024. “Analisis Sentimen Masyarakat Terhadap Isu Penundaan Pemilu 2024 Pada Twitter Dengan Metode Naive Bayes Dan Support Vector Machine.” Jurnal Sains Dan Teknologi 5(3):890–99. doi: 10.55338/saintek.v5i1.2789.
Haryanto, Budi, Yova Ruldeviyani, Fathur Rohman, T. N. Julius Dimas, Ruth Magdalena, and F. Muhamad Yasil. 2019. “Facebook Analysis of Community Sentiment on 2019 Indonesian Presidential Candidates from Facebook Opinion Data.” Pp. 715–22 in Procedia Computer Science. Vol. 161. Elsevier B.V.
Imam, Muhamad, and Syafii Informatika. 2023. SENTIMEN ANALISIS PADA MEDIA SOSIAL MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER (NBC). Vol. 3.
Imran, Bahtiar, Muh Nasirudin Karim, and Nur Isna Ningsih. 2024. KLASIFIKASI BERITA HOAX TERKAIT PEMILIHAN UMUM PRESIDEN REPUBLIK INDONESIA TAHUN 2024 MENGGUNAKAN NAÏVE BAYES DAN SVM.
Madjid, Marchenda Fayza, Dian Eka Ratnawati, and Bayu Rahayudi. 2023. “Sentiment Analysis on App Reviews Using Support Vector Machine and Naïve Bayes Classification.” Sinkron 8(1):556–62. doi: 10.33395/sinkron.v8i1.12161.
Mantik, Jurnal, Imam Rasyidin Muqsith Rizqi Prasetyo, and Aziz Musthafa. 2023. Comparison between Naive Bayes Method and Support Vector Machine in Sentiment Analysis of the Relocation of the Indonesian Capital. Vol. 7. Online.
Manullang, Oktaviami, Cahyo Prianto, and Nisa Hanum Harani. 2023. Analisis Sentimen Untuk Memprediksi Hasil Calon Pemilu Presiden Menggunakan Lexicon Based Dan Random Forest.
Robi Padri, Abdul, Asro Asro, and Indra Indra. 2023. “Classification of Traffic Congestion in Indonesia Using the Naive Bayes Classification Method.” Journal of World Science 2(6):877–88. doi: 10.58344/jws.v2i6.285.
Rosyida, Tamara, Harjono P. Putro, and Herry Wahyono. 2024. “ANALISIS SENTIMEN TERHADAP PILPRES 2024 BERDASARKAN OPINI DARI TWITTER MENGGUNAKAN NAÏVE BAYES DAN SVM.” Teknokris.
Saifullah Fattah, Fardhan, and Chanifah Indah Ratnasari. 2023. Sentiment Analysis of Indonesian Presidential Candidate 2024 on Facebook. Vol. 7. Fardhan Saifullah Fattah.
Salsabila, Fadila, and Utomo Budiyanto. 2023. IMPLEMENTASI NAÏVE BAYES CLASSIFIER TERKAIT PENCALONAN GANJAR PRANOWO SEBAGAI CALON PRESIDEN 2024 DI TWITTER. Vol. 2.
Saputra, Pramana Yoga, Dian Hanifudin Subhi, Fahmi Zain, and Afif Winatama. 2019. “IMPLEMENTASI SENTIMEN ANALISIS KOMENTAR CHANNEL VIDEO PELAYANAN PEMERINTAH DI YOUTUBE MENGGUNAKAN ALGORITMA NAÏVE BAYES.” Jurnal Informatika Polinema 5.
Setiawan, Rudi, and Fitria Dewi. 2023. “Analysis of Twitter User Sentiment on Presidential Candidate Anies Baswedan Using Naïve Bayes Algorithm.” ILKOM Jurnal Ilmiah 15(3):473–87. doi: 10.33096/ilkom.v15i3.1775.473-487.
Silalahi, William, and Adi Hartanto. 2023. “Klasifikasi Sentimen Support Vector Machine Berbasis Optimasi Menyambut Pemilu 2024.” JRST (Jurnal Riset Sains Dan Teknologi) 7(2):245. doi: 10.30595/jrst.v7i2.18133.
Tohidi, Edi, Reza Perdana Herdiansyah, and Edi Wahyudin. 2024. ANALISA SENTIMEN KOMENTAR VIDEO YOUTUBE DI CHANNEL TVONENEWS TENTANG CALON PRESIDEN PRABOWO SUBIANTO MENGGUNAKAN SUPPORT VECTOR MACHINE. Vol. 8.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Asro Asro, Nur Azizah, Sudaryono Sudaryono
This work is licensed under a Creative Commons Attribution 4.0 International License.
