Analisis Sentimen Pengguna Media Sosial Terhadap Identitas Kependudukan Digital Menggunakan Metode Support Vector Machine (SVM) - Sulistiani, Vina Alipah; Hamka, Muhammad (Journal of Information System Research (JOSH), 2024)
The Government of the Republic of Indonesia has implemented a policy of using Digital Population Identity (IKD) as one of the priority services of the Electronic Based Government System (SPBE) to accelerate digital transformation in the context of integrase national digital service. The implementation of IKD raises pros and cons perspectives in society. The counter perspective that is a problem in using IKD is that people are still worried about the security and privacy of personal data listed on digital systems. People can easily voice opinions, aspirations and participation through social media. However, given the large amount of social media data available, the process of obtaining the right information requires a lot of time and special skills. So a sentiment analysis of IKD on social media was carried out using the method Support Vector Machine (SVM) and improved with techniques Synthetic Minority Oversampling Technique (SMOTE) which aims to find out views or opinions regarding IKD which are positive, negative and neutral based on other people's points of view. The opinion data used in this research was 6697 with the keywords "digital population identity", "electronic ID card", and "digital ID card" taken from 2021 to 2024. Then, the data was classified based on polarity values ​​using a dictionary lexicon that is senticnet7 with sentiment results positive by 57.1% and sentiment negative amounting to 42.9%. The results of the classification process using the SVM method and enhanced with the SMOTE technique have results accuracy of 89%, negative precision of 88%, positive precision of 90%, recall negative by 85%, recall positive by 92%, f1-score negative by 86%, and f1-score positive by 91%.