Article Per Year (5 Year)
p-Index From 2021 - 2026
1.607
P-Index
This Author published in this journals
All Journal Indonesian Journal on Data Science Teknomatika: Jurnal Informatika dan Komputer
Alfun Roehatul Jannah
Unknown Affiliation
Computer Science & IT

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Metode Latent Dirichlet Allocation Untuk Menentukan Topik Pada Review Drama Korea Alfun Roehatul Jannah; Kristi, Ria; Muhammad Habibi
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 2 No. 1 (2024): Indonesian Journal on Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v2i1.1345

Abstract

The Hallyu Wave, involving the spread of South Korean culture and popular media, has rapidly grown over the past two decades. In addition to entertainment industries such as K-pop and K-drama, this phenomenon has also extended into the food and K-beauty sectors. Korean dramas, as the core of Hallyu, have become a global phenomenon with a continuously expanding fan base worldwide. A global survey in 2022 indicated that 36 percent of respondents in 26 countries considered Korean dramas very popular in their respective countries. In Indonesia, Korean films and dramas remain favorites, with 72 percent of streaming audiences choosing them on OTT services throughout 2022. Viu dominates as the most popular Korean drama streaming platform with 57 percent usage, followed by Netflix, Telegram, and WeTv. This research focuses on the analysis of Korean drama review data from 2015 to 2023 using the Latent Dirichlet Allocation (LDA) method. The goal is to provide a deep understanding of critical aspects such as acting, storyline, and cinematography. With LDA, this research aims to identify topics related to these elements, offering specific insights into audience preferences. From the conducted research, 10 ideal topics emerged out of 20 existing topics to ensure topic consistency using topic coherence. From the topic coherence results for these 20 topics, it can be concluded that the overall topic score for topic 10 is 0.527, providing ideal results for topic modeling in accordance with the rules.
Co-Authors Agung Priyanto Ahmad Hanafi Ahmad Hanafi Alfirna Rizqi Lahitani Anas Sufi Hasan Manahingati Ari Cahyono Arief Ikhwan Wicaksono Aris Wahyu Murdiyanto Choerun Asnawi Fatta Shofa Hasani Iqbal Hadi Subekti Kharisma Kristi, Ria Kusumaningtyas, Kartikadyota M Roykhul Jinan Meidiyanto Heri Pratama Muhammad Habibi Muhammad Habibi Puji Winar Cahyo Saputra, Andika Bayu SITI FATIMAH Syaifullah