Abstract
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%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
