ANALISIS SENTIMEN MENGENAI KESADARAN MASYARAKAT INDONESIA TERHADAP KEAMANAN SIBER DALAM MENGHADAPI KEBOCORAN DATA MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER - Dinna Nurfadlillah (Electro Luceat, 2023)
Leakage of personal data is a serious challenge, the adverse effects of incidents of data leakage can result in fines, loss of reputation and public trust that has been harmed. Cyber security plays a role in minimizing the level of risk of cyberattack threats that disrupt the security of all system components such as infrastructure, software, hardware and data. This research was conducted to analyze the sentiments of the Indonesian people towards the queries "cyber security" and "data leaks" from Twitter user tweets. The data classification in this study uses the Naïve Bayes Classifier algorithm method. The purpose of this study is to determine the percentage performance of positive and negative sentiments. The results of the modeling performance are obtaining accuracy percentage values of 88.80%, Precision 29.27%, and Recall 30.77%. The results of the data visualization show that Indonesian people, especially Twitter users, give many negative opinions in response to this discussion. So the percentage of negative sentiment is higher than positive sentiment.