Analisa Sentimen Penghapusan Tilang Manual Menjadi Tilang Elektronik Menggunakan Text Mining Dan TermFrequency Inverse Document Frequency (TF-IDF) - Pratiwi, Elsa (KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer), 2024)
Removing manual ticketing to electronic ticketing is a manual ticketing. Many people complain that the method of ticketing does not comply with procedures, there are misunderstandings in manual ticketing and in manual ticketing this is also an opportunity for extortion. The algorithms that will be used to support the removal of manual traffic tickets from electronic tickets are the Text Mining Algorithm and TF-IDF. The solution is to avoid errors in ticketing by holding electronic tickets using sophisticated CCTV where the image or video results are automatically saved and the data of drivers who violate traffic automatically displays the data of drivers who violate traffic. With the existence of electronic tickets, people are more compliant with traffic and the number of traffic violations has decreased. Using the Text Mining Algorithm and TF-IDF, you will get the results of the percentage of positive and negative sentiment from each public opinion comment via Twitter social media regarding the elimination of manual traffic tickets into electronic tickets, which in turn the results of the comments can be used as a reference for opinions from the results of the comments.