NLP, Machine Learning Optimizing Machine Learning in Natural Language Processing to Analyze User Sentiment in the Tiktok Social Media Application

Optimizing Machine Learning in Natural Language Processing to Analyze User Sentiment in the Tiktok Social Media Application

Authors

  • Fahmi Setiawan Universitas Pembangunan Panca Budi
  • Izhar Fradila
  • Alwi Pernando
  • Supina Batubara

DOI:

https://doi.org/10.61306/jitcse.v1i2.25

Keywords:

Machine Learning, NLP, Aplikasi Tiktok, Automation.

Abstract

This research aims to optimize the use of Machine Learning in Natural Language Processing (NLP) to analyze user sentiment in the social media application TikTok. The growth and development of the TikTok application among users, makes it important for users to understand users' views and feelings towards the content they consume by exploring various Machine Learning techniques that can be used to classify TikTok user sentiment based on text produced using NLP methods, it is hoped that this can provide useful insights. valuable in understanding TikTok users' responses and preferences to the content they encounter on the TikTok platform.

References

Greener, J. G., Kandathil, S. M., Moffat, L., & Jones, D. T. (2022). A guide to machine learning for biologists. Nature reviews Molecular cell biology, 23(1), 40-55.

Jaya, A. D. A. (2023). Optimalisasi Waktu Proyek Menggunakan Critical Path Methode (CPM) Pada Pembangunan Gedung DPRD Provinsi Kalimantan Utara.

KLANTIKA, D. B. (2023). ANALISIS OPTIMALISASI PROYEK DI PT. PRASETIA DWIDHARMA PADA PROYEK PENGADAAN ALAT GYM ST. REGIS JAKARTA MENGGUNAKAN METODE CRITICAL PATH METHODE (CPM) DAN PROJECT EVALUATION AND REVIEW TECHNIQUE (PERT) (Doctoral dissertation, Universitas Mercu Buana Jakarta).

Li, W., Wang, C. H., Cheng, G., & Song, Q. (2023). International conference on machine learning. Transactions on machine learning research.

Mandias, G. F. (2017). Analisis pengaruh pemanfaatan smartphone terhadap prestasi akademik mahasiswa Fakultas Ilmu Komputer Universitas Klabat. Cogito Smart Journal, 3(1), 83-90.

Min, B., Ross, H., Sulem, E., Veyseh, A. P. B., Nguyen, T. H., Sainz, O., ... & Roth, D. (2023). Recent advances in natural language processing via large pre-trained language models: A survey. ACM Computing Surveys, 56(2), 1-40.

Nadhif, I., Budiarto, U., & Iqbal, M. (2020). Optimasi Bentuk Buritan Kapal Perintis 750 DWT Menggunakan Response Surface Methode (RSM) untuk Mengurangi Hambatan. Jurnal Teknik Perkapalan, 9(1), 105-111.

Nizar Saeful Muslim, N. S. (2021). Pengaruh Kombinasi Suhu dan Lama Pengeringan Laru Tepung Jagung Putih dengan Tray Dryer Hasil Optimasi Response Surface Methode (RSM) (Doctoral dissertation, Universitas Sahid Jakarta).

Nugraha, A. C. (2020). Penerapan Teknologi Blockchain dalam Lingkungan Pendidikan: Studi Kasus Jurusan Teknik Komputer dan Informatika POLBAN. Produktif: Jurnal Ilmiah Pendidikan Teknologi Informasi, 4(1), 302-307.

Qin, C., Zhang, A., Zhang, Z., Chen, J., Yasunaga, M., & Yang, D. (2023). Is chatgpt a general-purpose natural language processing task solver?. arXiv preprint arXiv:2302.06476.

Rahmanto, Y., Ulum, F., & Priyopradono, B. (2020). Aplikasi pembelajaran audit sistem informasi dan tata kelola teknologi informasi berbasis Mobile. Jurnal Tekno Kompak, 14(2), 62-67.

Ramadhani, M. R., Aryadita, H., & Wicaksono, S. A. (2018). Analisis dan Perancangan Sistem Informasi Manajemen Donasi, Kegiatan, dan Relawan bagi Komunitas Sosial di Kota Malang (Studi Kasus: Komunitas TurunTangan Malang). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2(9), 3102-3109.

Tedjasuksmana, B. (2021, March). Optimalisasi Teknologi Dimasa Pandemi Melalui Audit Jarak Jauh Dalam Profesi Audit Internal. In Seminar Nasional Akuntansi dan Call for Paper (Vol. 1, No. 1, pp. 313-322).

Widyono, S. F., Hendrakusma, N., & Akbar, M. A. (2019). Perancangan User Interface Aplikasi Travelingyuk Berbasis Mobile Menggunakan Metode Human Centered Design (HCD). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 3(8), 7415-7424.

Wu, L., Chen, Y., Shen, K., Guo, X., Gao, H., Li, S., ... & Long, B. (2023). Graph neural networks for natural language processing: A survey. Foundations and Trends® in Machine Learning, 16(2), 119-328.

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Published

2024-07-03

How to Cite

Setiawan, F., Fradila, I., Pernando, A., & Batubara, S. (2024). NLP, Machine Learning Optimizing Machine Learning in Natural Language Processing to Analyze User Sentiment in the Tiktok Social Media Application: Optimizing Machine Learning in Natural Language Processing to Analyze User Sentiment in the Tiktok Social Media Application. Journal of Information Technology, Computer Science and Electrical Engineering, 1(2). https://doi.org/10.61306/jitcse.v1i2.25