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Salah satu media sosial yang sering membagikan berita dan popular digunakan di Indonesia adalah YouTube. Melalui platform YouTube pembaca dapat memberikan komentar untuk berbagi pendapat mereka dibawah vidio terkait. Komentar ini telah menjadi sumber informasi dan penelitian yang bagus. Artikel ini menyajikan kumpulan data yang berisi 368.299 komentar publik dan balasan dari 73 berita video yang diterbitkan dari 01 Januari 2024 hingga 18 Mei 2024 dari saluran “YouTube Indonesia Lawyers Club” yang terkenal. Sebagai upaya memastikan privasi komentator maka nama komentator dikodekan dalam dataset. Dataset ini terbuka untuk digunakan oleh para peneliti dengan link akses https://data.mendeley.com/datasets/h9335fgsgr/1. Data ini dapat membantu para peneliti untuk mengidentifikasi pola-pola dalam opini publik dan menganalisis apa isu yang populer dibiciarakan di chanel youtube Indonesia lawyers club tahun 2024. Hasilnya isu populer yang sering dibicarakan adalah terkait dengan pemerintahan Jokowi dan pemilu, sedangkan sentimen yang paling banyak dari isu tersebut adalah negatif yang menghasilkan nilai akurasi metode LSTM sebesar 99.61 % sedangkan dengan metode Bi-LSTM akurasinya sebesar 98.11 %.
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References
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- D. Mualfah, R. Gunawan, D. Mulyadipa Suratno, and A. Sentimen Komentar YouTube TvOne Tentang Ustadz Abdul Somad Dideportasi Dari Singapura Menggunakan, “Analisis Sentimen Komentar YouTube TvOne Tentang Ustadz Abdul Somad Dideportasi Dari Singapura Menggunakan Algoritma SVM,” J. FASILKOM, vol. 13, no. 01, pp. 72–80, Jul. 2023, doi: 10.37859/JF.V13I01.4920.
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- Nurmawiya and K. A. Harvian, “Public Sentiment Towards Face-to-Face Activities During the COVID-19 Pandemic in Indonesia,” Procedia Comput. Sci., vol. 197, pp. 529–537, Jan. 2022, doi: 10.1016/J.PROCS.2021.12.170.
- S. Srivastava, C. Chakraborty, and M. K. Sarkar, “Leveraging Machine Learning and Dimensionality Reduction for Sports And Exercise Sentiment Analysis,” Meas. Sensors, vol. 33, p. 101182, Jun. 2024, doi: 10.1016/J.MEASEN.2024.101182.
- A. Wahid and G. Saputri, “Analisis Sentimen Komentar Youtube Tentang Relawan Patwal Ambulance Menggunakan Algoritma Naïve Bayes dan Decision Tree,” J. Sist. Komput. dan Inform., vol. 4, no. 2, pp. 319–326, Dec. 2022, doi: 10.30865/json.v4i2.4941.
- M. S. Islam, M. A. T. Rony, M. Ahammad, S. M. N. Alam, and M. S. Rahman, “An Innovative Novel Transformer Model and Datasets for Safeguarding Religious Sensitivities in Online Social Platforms,” Procedia Comput. Sci., vol. 233, pp. 988–997, Jan. 2024, doi: 10.1016/J.PROCS.2024.03.288.
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References
K. Shanthi, “The Evolution of Authoritarian Digital Influence Grappling with the New Normal,” Prism, vol. 9, no. 1, pp. 32–51, 2020.
M. Yasir, M. Grace Haque, R. Suraji, and C. Author, “Analisis Sentimen Terhadap Kontroversi Fatwa MUI Nomor 83 Tahun 2023 Tentang Pemboikotan Produk yang Terafiliasi Israel,” J. Ekon. Manaj. Sist. Inf., vol. 5, no. 4, pp. 409–422, Mar. 2024, doi: 10.31933/JEMSI.V5I4.1845.
T. Daglis and K. P. Tsagarakis, “A Linkedin-Based Analysis Of The U.S. Dynamic Adaptations In Healthcare During The COVID-19 Pandemic,” Healthc. Anal., vol. 5, p. 100291, Jun. 2024, doi: 10.1016/J.HEALTH.2023.100291.
S. S. Zaidi, A. Perveen, M. A. Alam, J. Kishore, and U. D. Bhardwaj, “Study to Assess the Effectiveness of Behavioural Change Communication Aid for the Anger Management in Adolescents: A Quasi Experimental Study in the Selected Juvenile Aid Center, New Delhi,” Brain Behav. Immun. Integr., vol. 6, p. 100057, Apr. 2024, doi: 10.1016/J.BBII.2024.100057.
S. M. Alhashmi, I. A. T. Hashem, and I. Al-Qudah, “Artificial Intelligence applications in healthcare: A bibliometric and topic model-based analysis,” Intell. Syst. with Appl., vol. 21, p. 200299, Mar. 2024, doi: 10.1016/J.ISWA.2023.200299.
N. Novianty, S. Syarif, and M. Ahmad, “Influence of Breast Milk Education Media on Increasing Knowledge About Breast Milk: Literature Review,” Gac. Sanit., vol. 35, pp. S268–S270, Jan. 2021, doi: 10.1016/J.GACETA.2021.10.031.
A. Nastasa, T. C. Dumitra, and A. Grigorescu, “Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates,” Heliyon, vol. 10, no. 9, May 2024, doi: 10.1016/J.HELIYON.2024.E30412.
Z. M. Yusoff, N. Ismail, and S. A. Nordin, “Dataset for Five Recent Years (2019 – 2023) Agarwood Essential Oil Research Trends: A Bibliometric Analysis,” Data Br., vol. 54, p. 110310, Jun. 2024, doi: 10.1016/J.DIB.2024.110310.
M. Yang, J. He, L. Shi, Y. Lv, and J. Li, “Integrating policy quantification analysis into ecological security pattern construction: A case study of Guangdong–Hong Kong–Macao Greater Bay Area,” Ecol. Indic., vol. 162, p. 112049, May 2024, doi: 10.1016/J.ECOLIND.2024.112049.
R. Pils and P. Schoenegger, “Scientific Realism, Scientific Practice, and Science Communication: An Empirical Investigation of Academics and Science Communicators,” Stud. Hist. Philos. Sci., vol. 105, pp. 85–98, Jun. 2024, doi: 10.1016/J.SHPSA.2024.05.005.
L. H. Chowdhury, S. Islam, and S. Shatabda, “A Bengali News And Public Opinion Dataset From Youtube,” Data Br., vol. 52, p. 109938, Feb. 2024, doi: 10.1016/J.DIB.2023.109938.
Y. Dokuz, “Discovering Popular And Persistent Tags From Youtube Trending Video Big Dataset,” Multimed. Tools Appl., vol. 83, no. 4, pp. 10779–10797, Jan. 2024, doi: 10.1007/S11042-023-16019-Z/METRICS.
I. Rozi, S. Pramono, and E. Dahlan, “Implementasi Opinion Mining (Analisis Sentimen) Untuk Ekstraksi Data Opini Publik Pada Perguruan Tinggi,” J. EECCIS, vol. 6, no. 1, pp. 37–43, 2012.
R. Gerung, “Pengetahuan Membebaskan Kita dari Opini yang Keliru,” Jurnal Perempuan, p. 1, 2017. Accessed: Oct. 24, 2024. [Online]. Available: https://www.jurnalperempuan.org/warta-feminis/rocky-gerung-pengetahuan-membebaskan-kita-dari-opini-yang-keliru
E. Effendy, Zakaria, Azlisa, and Anggarana, “Dasar Dasar Penulisan Berita,” J. Pendidik. dan Konseling, vol. 5, no. 2, pp. 4042–4044, 2023, [Online]. Available: https://journal.universitaspahlawan.ac.id/index.php/jpdk/article/view/13888
V. A. Fitri, R. Andreswari, and M. A. Hasibuan, “Sentiment Analysis of Social Media Twitter with Case of Anti-LGBT Campaign in Indonesia using Naïve Bayes, Decision Tree, and Random Forest Algorithm,” Procedia Comput. Sci., vol. 161, pp. 765–772, Jan. 2019, doi: 10.1016/J.PROCS.2019.11.181.
H. Nurrifqi, F. Fikrillah, and D. Kurniadi, “Rekomendasi Pemilihan Program Studi Menggunakan Algoritma Naïve Bayes,” J. Algoritm., vol. 20, no. 1, pp. 42–49, May 2023, doi: 10.33364/ALGORITMA/V.20-1.1236.
A. Karimah, G. Dwilestari, and M. Mulyawan, “Analisis Sentimen Komentar Video Mobil Listrik Di Platform Youtube Dengan Metode Naive Bayes,” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 1, pp. 767–737, Mar. 2024, doi: 10.36040/JATI.V8I1.8373.
P. Y. Saputra, D. H. Subhi, and Fahmi Zain Afif Winatama, “Implementasi Sentimen Analisis Komentar Channel Video Pelayanan Pemerintah Di Youtube Menggunakan Algoritma Naïve Bayes,” J. Inform. Polinema, vol. 5, no. 4, pp. 209–213, Aug. 2019, doi: 10.33795/jip.v5i4.259.
D. Mualfah, R. Gunawan, D. Mulyadipa Suratno, and A. Sentimen Komentar YouTube TvOne Tentang Ustadz Abdul Somad Dideportasi Dari Singapura Menggunakan, “Analisis Sentimen Komentar YouTube TvOne Tentang Ustadz Abdul Somad Dideportasi Dari Singapura Menggunakan Algoritma SVM,” J. FASILKOM, vol. 13, no. 01, pp. 72–80, Jul. 2023, doi: 10.37859/JF.V13I01.4920.
S. Mujahidin, B. Prasetio, and M. C. C. Utomo, “Implementasi Analisis Sentimen Masyarakat Mengenai Kenaikan Harga BBM Pada Komentar Youtube Dengan Metode Gaussian naïve bayes,” Voteteknika (Vocational Tek. Elektron. dan Inform., vol. 10, no. 3, pp. 17–24, Sep. 2022, doi: 10.24036/VOTETEKNIKA.V10I3.118299.
Nurmawiya and K. A. Harvian, “Public Sentiment Towards Face-to-Face Activities During the COVID-19 Pandemic in Indonesia,” Procedia Comput. Sci., vol. 197, pp. 529–537, Jan. 2022, doi: 10.1016/J.PROCS.2021.12.170.
S. Srivastava, C. Chakraborty, and M. K. Sarkar, “Leveraging Machine Learning and Dimensionality Reduction for Sports And Exercise Sentiment Analysis,” Meas. Sensors, vol. 33, p. 101182, Jun. 2024, doi: 10.1016/J.MEASEN.2024.101182.
A. Wahid and G. Saputri, “Analisis Sentimen Komentar Youtube Tentang Relawan Patwal Ambulance Menggunakan Algoritma Naïve Bayes dan Decision Tree,” J. Sist. Komput. dan Inform., vol. 4, no. 2, pp. 319–326, Dec. 2022, doi: 10.30865/json.v4i2.4941.
M. S. Islam, M. A. T. Rony, M. Ahammad, S. M. N. Alam, and M. S. Rahman, “An Innovative Novel Transformer Model and Datasets for Safeguarding Religious Sensitivities in Online Social Platforms,” Procedia Comput. Sci., vol. 233, pp. 988–997, Jan. 2024, doi: 10.1016/J.PROCS.2024.03.288.
S. Kaur, S. Singh, and S. Kaushal, “Deep Learning-Based Approaches For Abusive Content Detection And Classification For Multi-Class Online User-Generated Data,” Int. J. Cogn. Comput. Eng., vol. 5, pp. 104–122, Jan. 2024, doi: 10.1016/J.IJCCE.2024.02.002.
M. Lestandy and Abdurrahim, “Exploring the Impact of Word Embedding Dimensions on Depression Data Classification Using BiLSTM Model,” Procedia Comput. Sci., vol. 227, pp. 298–306, Jan. 2023, doi: 10.1016/J.PROCS.2023.10.528.
B. P. Nayoga, R. Adipradana, R. Suryadi, and D. Suhartono, “Hoax Analyzer for Indonesian News Using Deep Learning Models,” Procedia Comput. Sci., vol. 179, pp. 704–712, Jan. 2021, doi: 10.1016/J.PROCS.2021.01.059.
D. Priadana, Sidik; dan Sunarsi, “Metode Penelitian Kuantitatif,” in Education, 1st ed., Tanggerang Selatan: Pascal Books, 2021, ch. 1, pp. 1–215.
R. Akbar, R. A. Siroj, M. Win Afgani, and U. Islam Negeri Raden Fatah Palembang Abstract, “Experimental Research Dalam Metodologi Pendidikan,” J. Ilm. Wahana Pendidik., vol. 9, no. 2, pp. 465–474, Jan. 2023, doi: 10.5281/ZENODO.7579001.
C. Li et al., “Pyvisvue3d3: Python Visualization From Hierarchy Tree To Call Graph,” SoftwareX, vol. 26, p. 101689, May 2024, doi: 10.1016/J.SOFTX.2024.101689.