Design and Build a Sentiment Prediction System for Public Opinion Regarding the 2024 Presidential Election Using Google Natural Language - aditya, Gusti Komang Wisnu; Putri, Gusti Agung Ayu; Mandeni, Ni Made Ika Marini (JITTER : Jurnal Ilmiah Teknologi dan Komputer, 2025)
In today's digital era, social media has become the primary platform for the public to express their political views and opinions. This study aims to analyze public sentiment ahead of the 2024 Presidential Election in Indonesia by utilizing Natural Language Processing (NLP) technology. Based on the analysis of social media data, various positive, neutral, and negative sentiments toward the presidential candidates were identified, with a dominant tendency towards positive sentiment. The developed prediction system was tested through the Post-Study System Usability Questionnaire and Black Box testing, which demonstrated ease in data retrieval, graph visualization, and sentiment management. This study provides important insights into the dynamics of political opinions and recommends further development to enhance analysis accuracy and integrate the latest technologies, which could open opportunities for more advanced information systems in the future.