PREDIKSI JUMLAH PENONTON VIDEO YOUTUBE MENGGUNAKAN MODEL DEEP NEURAL NETWORK (DNN)
Abstract
Youtube viewer becomes a major factor in a content creator's success. The problem is how can predict the number of viewers of a youtube content to determine the success of a content or make it a trending video topic. A machine or computer can predict the number of viewers using the ANN method. DNN is one of ANN models that can predict a dataset. This study compared the success rate in predicting the number of viewers of youtube content from Youtube API dataset. DNN model prediction results have a higher level of excellence compared to the use of traditional methods Linear Regression and Naive Bayes.
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References
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[13] Manisha, S. K. Dhull, and K. K. Singh, “ECG Beat Classifiers: A Journey from ANN to DNN,” in Procedia Computer Science, 2020, vol. 167, doi: 10.1016/j.procs.2020.03.340.
[14] R. Sharma, “YouTube Trending Video Dataset (US Region),” kaggle, 2020. https://www.kaggle.com/rsrishav/youtube-trending-video-dataset/.
[15] A. Shrestha and A. Mahmood, “Review of deep learning algorithms and architectures,” IEEE Access, vol. 7. 2019, doi: 10.1109/ACCESS.2019.2912200.
Published
2021-06-20
How to Cite
INDRAWAN, Dwin et al.
PREDIKSI JUMLAH PENONTON VIDEO YOUTUBE MENGGUNAKAN MODEL DEEP NEURAL NETWORK (DNN).
JISICOM (Journal of Information System, Informatics and Computing), [S.l.], v. 5, n. 1, p. 94-98, june 2021.
ISSN 2597-3673.
Available at: <https://journal.stmikjayakarta.ac.id/index.php/jisicom/article/view/463>. Date accessed: 18 apr. 2024.
doi: https://doi.org/10.52362/jisicom.v5i1.463.
Section
Articles
This work is licensed under a Creative Commons Attribution 4.0 International License.
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