Analisis Sentimen Netizen Terhadap Efisiensi APBN Menggunakan Orange Data Mining
DOI:
https://doi.org/10.47467/elmujtama.v5i3.7368الكلمات المفتاحية:
Orange Data Mining, Text Mining, APBN Efficiency, Naïve Bayes, Sentiment Analysisالملخص
The government's policy of APBN efficiency in 2025 has caused debate on social media including the X application (Twitter). Social media users and activists convey comments and opinions according to their respective sentiments, whether they agree, disagree, or are neutral towards government policies. This study will try to analyze sentiment on netizens' opinions and views using the Orange Data Mining application with the Sentiment Analysis - Multilingual Sentiment method. Testing is also carried out using the Naïve Bayes algorithm to measure the level of accuracy and prediction error. The results of the sentiment analysis in this study are that most support the APBN efficiency policy with a level of confidence and accuracy approaching 100%.
التنزيلات
التنزيلات
منشور
كيفية الاقتباس
إصدار
القسم
الرخصة
الحقوق الفكرية (c) 2025 Anto Febria, Joko Triloka

هذا العمل مرخص بموجب Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.




