ANALISIS SENTIMEN NETIZEN TERHADAP EFISIENSI APBN MENGGUNAKAN ORANGE DATA MINING

Febria, Anto and Triloka, Joko (2025) ANALISIS SENTIMEN NETIZEN TERHADAP EFISIENSI APBN MENGGUNAKAN ORANGE DATA MINING. ANALISIS SENTIMEN NETIZEN TERHADAP EFISIENSI APBN MENGGUNAKAN ORANGE DATA MINING, 7 (2). ISSN ISSN: 2685-9556

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Abstract

The government's policy on APBN efficiency in 2025 has sparked debate on social media, including the X platform (formerly Twitter). Social media users and activists express their opinions based on their respective sentiments—whether in support, opposition, or neutrality toward the policy. This study aims to analyze public sentiment on the issue using the Orange Data Mining application with the Sentiment Analysis - Multilingual Sentiment method. The Naïve Bayes algorithm is also applied to assess accuracy and prediction errors. The sentiment analysis results indicate that the majority support the APBN efficiency policy, with confidence and accuracy nearing 100%. Keywords: Orange Data Mining; Text Mining; APBN Efficiency; Naïve Bayes; Sentiment Analysis.

Item Type:	Article
Subjects:	Ilmu Komputer eTheses
Divisions:	Pasca Sarjana > Magister Teknik Informatika
Depositing User:	Febria Anto Febria
Date Deposited:	07 May 2025 06:51
Last Modified:	07 May 2025 06:51
URI:	http://repo.darmajaya.ac.id/id/eprint/20158

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