Sentiment Analysis on the Impact of Artificial Intelligence (AI) Development to Determine Technology Needs - Abror, Naufal; Novita, Rice; Mustakim; Afdal, M.Afdal (Jurnal Sistem Cerdas, 2024)
Artificial Intelligence (AI) has become a hot topic in recent years in Indonesia. To determine the influence of AI developments in determining technology needs, a sentiment analysis needs to be carried out. Sentiment analysis is a process used to help identify the contents of a dataset in the form of opinions or views (sentiments) in text form regarding an issue or event that is positive, negative or neutral. The algorithm applied in this research is the Multinominal Naive Bayes Classifier method. The Multinominal Naive Bayes Classifier method was chosen because it has quite high processing speed and accuracy when used on large, varied and large amounts of data. In this research, the sentiment results were "Negative" for the topic of data security and privacy with a testing accuracy of 75%, "Positive" for Economic Topics with a testing accuracy of 50%, "Negative" for Industrial Topics with a testing accuracy of 58%, "Positive" for Field Topics jobs with a testing accuracy of 75%, “Negative” Transportation Topics with a testing accuracy of 50%, and “Negative” for Education Topics with a testing accuracy of 67%.