Sentiment Analysis On Police Brigadier Shooting Case Using K-Means Clustering - Wahyuni , Masri; Rambe, Basyit Mubarroq; Br Tarigan , Yuni Franciska; Gultom , Karyawaty (Journal of Technology and Computer, 2024)
As a medium that can be used to convey public criticism and aspirations in real time, Twitter is used as a data collection source using crawling techniques, to analyze public sentiment or response to the police brigadier shooting case. Latent dirichlet al-location (LDA) is used to determine the topics that appear in each of the collected tweets, and then used as a feature in grouping the contents of the tweets based on their respective sentiment values. The results of clustering using the k-means clustering algorithm obtained are: 11.9% of netizens gave a positive response, 18.9% of netizens gave a neutral response and 69.2% of netizens gave a negative response to the case. Thus, from the results of this study it can be concluded that netizens tend to give a negative response or reaction to the police brigadier shooting case, when viewed from the percentage of each type of response.