CD Skripsi
Pemodelan Topik Genshin Impact Di Twitter/X Menggunakan Metode Latent Dirichlet Allocation
Video games is a part of the entertainment industry that continues to grow and loved by everyone. Developers are competing to create games that can attract players by evolution of video game. Hoyoverse is a company from China that develops animation and video games. One of the video games made by Hoyoverse is Genshin Impact. Opinions or judgments from players are needed for developing game. Topic modeling is one of text processing method to determine the dominant topic from big data. Topic modeling used to found the dominant topics were often discussed by players. The method that used for Genshin Impact topic modeling was latent Dirichlet allocation. The data used consisted of 5000 Twitter data. Topic modeling was carried out with the help of the Gensim library. From the results of this research, 5 topics were obtained with a coherence score of 0.603884. The 5 topics were interpreted about Streaming update fountain for topic 1, topic 2 about the community comparing Genshin Impact and Honkai Star Rail, topic 3 about Interaction between players in the Genshin Impact community, topic 4 about Comparing new and old characters, Topic 5 about characters in Genshin Impact.
Keywords : Genshin Impact, Latent Dirichlet Allocation, Topic Modelling.
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