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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Buletin Udayana Mengabdi Krisna: Kumpulan Riset Akuntansi Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Sistem dan Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Information Systems and Informatics Jurnal Informatika
Dwi Rusjayanthi, Dwi
Jurusan Teknologi Informasi, Fakultas Teknik, Universitas Udayana, Bali, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering

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Analisis Sentimen Masyarakat terhadap Tayangan Televisi Nasional menggunakan Metode Deep Learning Ferhati Bouchra; I Made Agus Dwi Suarjaya; Ni Kadek Dwi Rusjayanthi
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v15i2.9118

Abstract

Indonesia’s television industry faces fierce competition, particularly in chasing ratings and ad revenue. This has ultimately led to declining broadcast quality on some national TV stations. This research aims to understand perceptions towards content quality by focusing on public opinion through sentiment analysis of social media (Twitter) using Bi-LSTM and Word2Vec methods. The research involved data collection, preprocessing, vectorization, data splitting, model training and testing, evaluation to find the best model, sentiment data classification, and finally, sentiment data analysis. Using a dataset of 515,492 sentiment points, the model achieved an accuracy of 96.4%, precision of 72.1%, recall of 72.0%, and f1-score of 72.8%. Analysis of Twitter user sentiment leans towards neutral and positive perceptions. The results of the sentiment analysis of Twitter users tend to be neutral and positive. The results of the public satisfaction trend show a change in the pattern of public satisfaction with the quality of television station content.
Co-Authors A.A. K. O. Sudana A.A.K.O. Sudana Anak Agung Ketut Agung Cahyawan Wiranatha Anak Agung Kompiang Oka Sudana Anak Agung Ngurah Aditya Winata Anjela Faye M. Basco Apriana, Krisna Ayu Wirdiani D.P. Githa Desak Ayu Savita Desy Purnami Singgih Putri Dewa Gede Anom Surya Praktiyasa Dewa Putu Andre Sanjaya Ferhati Bouchra G M Arya Sasmita G.A.A. Putri Gede Eridya Bayu Gede Yudha Prema Pangestu Gembong Satria Prabowo Gusti Agung Ayu Putri I Dewa Made Endiana I Gusti Ngurah Indra Mahathanaya I Ketut Adi Purnawan I ketut Gede Darma Putra I Made Agus Dwi Suarjaya I Made Dwi Cahaya Putra I Made Sukarsa I Made Sukarsa I Made Suwija Putra I Made Suwija Putra I Nyoman Piarsa I Putu Adi Purnawan I Putu Agung Bayupati I Putu Arya Putra Wibawa I Putu Kerta Yasa I Putu Mahendra Pramadhitya Kadek Dede Hendra Kusuma Kevin Wijaya Luh Kade Devi Dwiyani Made Henny Aryani Made Santika Putra Made Srinitha Millinia Utami N.K.A. Wirdiani N.KA. Wirdiani Ngakan Nyoman Pandika Pinata Ngurah Arya Bhaskara Wardhana Ni Komang Widyasanti Ni Luh Putu Natha Primadewi Ni Luh Putu Yonita Putri Utami Ni Made Ika Marini Mandenni Ni Wayan Wisswani Paramartha, Ary Putra, I Putu Mega Juli Semara Putu Jhonarendra Putu Ratih Wulandari Ranis Cinthianingrum Shilta Inda Qurroti A'yun Achmadi Siluh Putu Natha Primadewi Wan Siti Maisarah Binti Mohd Luthfi Y. Haryo Sulistyanto Sunaryo