| dc.description.abstract | Data security has become a primary concern alongside rapid technological
advancements. Managing and protecting data, especially on a large scale with thorough
analysis, is crucial to prevent losses and safeguard the confidentiality of users' important
documents. Modern technology and societal lifestyles support various studies enabling
computers to understand, manipulate, and interpret human language. This research aims to
analyze sentiments within application X regarding data security, particularly concerning
incidents of breaches at the Temporary National Data Center (PDNS), using the Naïve Bayes
Classifier algorithm. The data consists of Indonesian-language tweets collected within
specific time frames using the keywords "pdns" and "pdns 2". This method is expected to
provide deeper insights into public perceptions of data security context, including sentiment
classifications such as positive, negative, and neutral visualized through graphs and word
clouds. The findings of this study are anticipated to contribute to a better understanding of
sentiment analysis on data security within application X and serve as a foundation forfurther
research in related fields. | en_US |
