PUBLIC SENTIMENT ANALYSIS OF THE INDONESIAN GOVERNMENT BUDGET EFFICIENCY NEWS USING VADER (VALENCE AWARE DICTIONARY AND SENTIMENT REASONER) ADAPTED TO THE INDONESIAN LANGUAGE LEXICON - Satria, Fiqih; Husaini, M. (Asia Information System Journal, 2025)
The Indonesian government's budget efficiency policy in 2025 has become a topic of wide public discussion, especially on social media. This study aims to analyze public sentiment towards the news of government budget efficiency using a text mining method based on Valence Aware Dictionary and sEntiment Reasoner (VADER) that has been adapted to the Indonesian language lexicon. Data was collected from YouTube comments using the YouTube API V3, with a total of 500 comments from the five videos that received the most responses. After preprocessing, word cloud, bigram, and trigram analyses showed that people highlighted various aspects of the policy, including the effectiveness of budget efficiency, transparency, and its impact on people's welfare. The sentiment analysis results showed that 41% of the comments were positive, 30% were negative, and 29% were neutral. Positive sentiments were mainly related to support for programs such as the Free Nutritious Meal (MBG) and bureaucratic retrenchment. Negative sentiments reflect criticism of alleged budget waste, an overly large cabinet, and skepticism about policy implementation. Meanwhile, neutral comments were generally informative or questioned the policy without showing a clear trend of opinion. This research shows that public discussion on government budget efficiency centers not only on the policy itself, but also on public perceptions of government performance and budget transparency. These findings can inform policymakers to improve public communication and ensure effective and transparent implementation of budget efficiency.