Analisis Sentimen Hasil Pemilu (Quick Count) Calon Presiden dan Wakil Presiden 2024 di Media Sosial Media X Menggunakan Metode Bidirectional Long Short-Term Memory (BiLSTM) - Aini, Qurrotu; Hidayat, M. Noer Fadli; Tholib, Abu (Forum Kerjasama Pendidikan Tinggi (FKPT), 2024)
It is important to understand public opinions, attitudes and sentiments in relation to presidential and vice presidential candidates in the context of Indonesia's general elections. The fact that quick count results have become a major topic of conversation on social media, especially on platforms such as Twitter, shows how important it is to monitor people's views on election results. However, tweets that are free-form and use digital language are often difficult for the unfamiliar to understand, which can lead to the spread of misinformation or inaccurate views. Sentiment analysis is therefore key in understanding people's views on election results. This research proposes the use of the Bidirectional Long Short Term-Memory (BiLSTM) method to analyse sentiment related to the quick count results of the 2024 presidential and vice presidential elections on X social media. This sentiment analysis aims to classify texts into positive, negative, or neutral categories. The purpose of this study is to measure the sentiment value and accuracy of the BiLSTM method in sentiment analysis of election results. Data was collected by scraping X social media using the keywords