Analisis Sentimen Masyarakat Terhadap Rencana Kenaikan PPN 12% Di Indonesia Pada Media Sosial X Menggunakan Metode Decision Tree - Intan Diah Hardyatman; Firman Noor Hasan (Journal of Information System Research (JOSH), 2025)
This study analyzes public sentiment towards the planned increase of Value Added Tax (VAT) to 12% in Indonesia using data from X social media. The VAT hike could trigger an increase in overseas spending and higher prices for products and services in Indonesia, potentially reducing sales and weakening industries. This proposal also received widespread attention on social media X. The VAT increase plan has pros and cons, triggering many discussions on social media. The Decision Tree classification method was used to process the data obtained through crawling and text preprocessing. This research compares 80% training data and 20% test data consisting of 1000 data, with details of 285 negative sentiments and 715 positive sentiments in the dataset. In this case, it can be described that X social media users towards the plan to increase VAT by 12% in Indonesia tend to be positive. This research aims to analyze people's sentiment towards the plan to increase VAT by 12% in Indonesia using Decision Tree and identify factors that influence the sentiment. The results of the analysis show that Decision Tree succeeded in increasing the accuracy by 81.34% of sentiment classification compared to previous methods, such as Naïve Bayes with an accuracy rate of 63.1%. The results of this study are expected to help the government in a more responsive fiscal policy.