ANALISIS SENTIMEN TERHADAP IDENTITAS KEPENDUDUKAN DIGITAL MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE

Since its release on June 3, 2022, Identitas Kependudukan Digital has become one of the most discussed topics among the public. Identitas Kependudukan Digital is a form of digitization of e-KTP. The public made various comments through many media, one of which was through Facebook social media. Not only supportive comments, but many comments are also critical. For this problem, sentiment analysis was carried out with the algorithm used for classification, namely the Support Vector Machine algorithm. Sentiment analysis is used to determine and obtain public responses to Identitas Kependudukan Digital, whose final results are expected to find solutions to the problems that occur. Community responses in the dataset are divided into three sentiments: positive, negative, and neutral. The processing results obtained 78.3% negative sentiment, 13.0% neutral sentiment, and 8.8% positive sentiment. To increase the level of accuracy, TF-IDF is used so that the accuracy value of using the Support Vector Machine algorithm is 77% with a precision value of 92%, a recall value of 37%, and an f1-score value of 35%.

Keywords: Identitas Kependudukan Digital, Sentiment Analysis, Support Vector Machine