Analisis Sentimen Netizen Terhadap Efisiensi APBN Menggunakan Orange Data Mining

المؤلفون

  • Anto Febria Institut Bisnis dan Informatika Darmajaya, Bandar Lampung, Indonesia
  • Joko Triloka Institut Bisnis dan Informatika Darmajaya, Bandar Lampung, Indonesia

DOI:

https://doi.org/10.47467/elmujtama.v5i3.7368

الكلمات المفتاحية:

Orange Data Mining, Text Mining, APBN Efficiency, Naïve Bayes, Sentiment Analysis

الملخص

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

بيانات التنزيل غير متوفرة بعد.

التنزيلات

منشور

2025-05-01

كيفية الاقتباس

Anto Febria, & Joko Triloka. (2025). Analisis Sentimen Netizen Terhadap Efisiensi APBN Menggunakan Orange Data Mining. El-Mujtama: Jurnal Pengabdian Masyarakat , 5(3), 477 –. https://doi.org/10.47467/elmujtama.v5i3.7368