Analisa Sentimen Undang-Undang Penganiyaan Menerapkan Algoritma Text Mining Dan TF-IDF - Endhika, Endhika (STMIK Budi Darma, 2024)
People's views on this article, some people think it is necessary because it is important to avoid acts of sexual violence, but some people think the article is not necessary because they think this is a normal thing which is actually considered a trivial thing but can become a behavior. acts of sexual harassment. The problem is that when someone whistles at someone without permission or with disrespectful intentions, it can be considered annoying or inappropriate. It is important to respect personal boundaries and treat others with respect. These views cause uproar in society. Therefore, there is a solution, namely in the form of a solution used in the Text Mining Algorithm to discover new information that was previously unknown and extract valuable information from text automatically from different sources, while the TF-IDF Algorithm is used to determine the frequency value of words. in the document. In this research, sentiment refers to the public's view of the Persecution Law, whether positive or negative. The final result of this sentiment analysis is a positive sentiment value of 56.746% while the negative sentiment value is 43.254%. So it is hoped that it can provide information about the extent to which the Persecution Law can be accepted by society by understanding public sentiment. Apart from that, this research also conceptualizes the Text Mining Algorithm and the TF-IDF Algorithm as powerful tools for analyzing text data in the context of sentiment analysis.