Analisis sentiment komentar Instagram bakal calon presiden menggunakan metode Support Vector Machine - Alqis Rausanfita; Ramadan, Arip; Dzulfikar Fauzi, Muhammad; Mafidah, Qori Emalia Putri; Ramona, Emilia; Mahardika Putra, Yudha (Fakultas Sains dan Teknologi-Universitas Buddhi Dharma, 2023)
The rising number of Instagram user affecting higher number of comments appear on post especially Instagram accounts of Indonesia's 2024 presidential candidates that made it difficult to understand the public sentiment towards presidential candidate. Therefore, this research aims to classify Indonesian sentiment on Instagram comments of 2024 Indonesian presidential candidates using the Support Vector Machine method. The classified sentiment is divided into three classes, namely positive, negative, and neutral. The results shows that Sentiment Analysis of Comments on Instagram Posts of Indonesia's 2024 Presidential Candidates Using The Support Vector Machine Method has a good accuracy value of 89.41%. This results also obtain recall and precision values of 89% and 87% respectively.