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SENTIMENT ANALYSIS OF X PLATFORM ON VIRAL'FUFUFAFA' ACCOUNT ISSUE IN INDONESIA USING SVM
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In this study, we conducted a comprehensive sentiment analysis of users on the social
media platform X concerning the viral controversy surrounding the KasKus account knownas “Fufufafa.” This issue attracted widespread attention and sparked varied reactions withinthe online community. To gain insights into public opinion on the topic, we utilized theSupport Vector Machine (SVM) method, a widely recognized machine learning algorithmfor
classification tasks. The data for this research was gathered from various posts, comments, and public discussions on platform X, which were pre-processed to filter out irrelevant
information, such as spam, unrelated topics, and non-informative content. After cleaning thedata, user sentiments were categorized into three primary classes: positive, negative, andneutral. The SVM model was then trained and tested using a labeled dataset to accuratelypredict user sentiments based on the textual content of their interactions. Through this
approach, we aimed to capture the overall mood and attitudes of the online communitytowards the "Fufufafa" issue. The findings of the study reveal that the majority of users onplatform X expressed negative sentiments about the viral controversy, suggestingdissatisfaction or disapproval. Meanwhile, a smaller portion of the users remained neutral, while an even smaller segment displayed positive sentiment. This disparity highlights thepolarized reactions within the online discourse. Our study also demonstrates the ef icacy of
the SVM method in analyzing large-scale social media data to understand public sentiment onviral issues. Ultimately, this research of ers a valuable contribution to understanding howusers on social media respond to controversial topics and trending events. Keywords— Sentiment Analysis, X, SVM, Fufufafa, Indonesia
Suryanto, - 23/1009/0091/TSD/02 - Personal Name
Dr. Widyastuti Andriyani, S.Kom., M.Kom. - Personal Name
Dr. Widyastuti Andriyani, S.Kom., M.Kom. - Personal Name
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Text Skripsi
Indonesia
UNIVERSITAS TEKNOLOGI DIGITAL INDONESIA (UTDI)
2025
Yogyakarta
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