Social Media Sentiment Analysis of Instagram Use by Early Childhood Education Information System Development Based on Naïve Bayes - Yuma Akbar; Sugiyono Sugiyono; Dedi Gunawan; Salsabila Putri Wibowo (Asosiasi Riset Teknik Elektro dan Infomatika Indonesia, 2026)
This study employs the Naïve Bayes method to analyze social media sentiment regarding the use of Instagram by early childhood users. The primary objective of this research is to understand public perceptions of the positive and negative impacts of Instagram usage among young children, particularly in relation to their social, psychological, and digital behavioral development. Sentiment analysis is carried out using data from various social media platforms, which are then classified into positive, negative, and neutral opinions. The classification results form the basis for developing an integrated educational information system designed to provide guidance for parents, educators, and children in using Instagram safely, healthily, and responsibly. The system also emphasizes the importance of age-appropriate content education, privacy settings, and strategies to minimize the risks of exposure to inappropriate content and the negative effects of excessive usage. This research is expected to support the creation of a more positive, safe, and beneficial digital environment for early childhood users while also serving as a reference in formulating effective policies in the social media era.