ANALISIS SENTIMENT PUBLIC TERHADAP KEPUTUSAN MK MENGENAI BATAS USIA KANDIDAT CAPRES DAN CAWAPRES BERDASARKAN MEDIA SOSIAL TWITTER MENGGUNAKAN METODE VADER (VALENCE AWARE DICTIONARY AND SENTIMENT REASONER) - Fitri, Aulia Alqusyah; Perdana, Andreas (Jurnal TAM (Technology Acceptance Model), 2024)
There is a lot of discussion on Twitter about the decision of the Constitutional Court (MK) regarding the age limit for presidential and vice presidential candidates. The abundance of tweets on Twitter has made it difficult to determine the intended meaning of each tweet, whether it is negative, positive, or neutral. Therefore, sentiment analysis is needed to easily interpret the meaning of each tweet, whether it is negative, positive, or neutral. In this research, sentiment analysis techniques will be used by labeling tweets using VADER (Valence Aware Dictionary and Sentiment Reasoner) to find out how the public responded to the Constitutional Court's decision regarding the age limit for presidential and vice presidential candidates.  A total of 2621 tweet data were obtained through data crawling using web scraping with the Google Colab application and utilizing the Python programming language, then analyzed and visualized using VADER (Valence Aware Dictionary and Sentiment Reasoner). The research results indicate that the majority of the public response, accounting for 90.35%, is neutral sentiment, 6.02% negative sentiment, and 3.63% positive sentiment. The predominance of neutral sentiment may occur because many tweets only convey facts without including opinions or evaluations, or texts that are descriptive in nature without expressing emotions or evaluations, thereby tending to be considered neutral by the VADER algorithm.