ANALISIS SENTIMEN KEBIJAKAN WFH BAGI ASN MENGGUNAKAN ALGORITMA SVM DI MEDIA SOSIAL X
DOI:
https://doi.org/10.59819/jmti.v6i2.7056Keywords:
Analisis Sentimen, Support Vector Machine, Work From Home, Media Sosial X, Sentiment Analysis, Support Vector Machine, TF-IDF, Work From Home, Civil ServantsAbstract
The implementation of the Work From Home (WFH) policy for Civil State Apparatus (ASN) has generated various public opinions on social media X. This study aims to analyze public sentiment toward the WFH policy using the Support Vector Machine (SVM) algorithm. The dataset consists of 1,300 tweets collected from social media X and processed through text preprocessing, TF-IDF weighting, and sentiment classification. The results show that the SVM algorithm achieved high classification performance in distinguishing positive and negative sentiments toward the WFH policy. This study demonstrates that SVM is effective for sentiment analysis of Indonesian-language social media data and can support policy evaluation based on public opinion.
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