Hoax News Analysis for the Indonesian National Capital Relocation Public Policy with the Support Vector Machine and Random Forest Algorithms

Abstract

The decision of the Indonesian government to relocate the nation's capital outside Java to the North Penajam Paser Regency has sparked controversy and misinformation on social media platforms. While sentiment analysis studies have been conducted on this topic, no research has yet analyzed the issue of hoaxes related to the relocation of the national capital. This study aims to fill this gap by analyzing hoaxes related to the relocation of the Indonesian national capital on Twitter. The study utilizes data crawling, filtering with Hoax Booster Tools (HBT) ASE, data labeling, preprocessing, and TF-IDF weighting. The data is then classified using Support Vector Machine (SVM) and Random Forest (RF) algorithms, and the results of both algorithms are compared. The study found that 85% of tweets had a positive sentiment and 15% had a negative sentiment. Furthermore, the SVM algorithm outperformed the RF algorithm with an accuracy of 95.24% compared to 86.90%. This study contributes to the understanding of the hoax issues related to the relocation of the Indonesian state capital and provides recommendations for government policies to address community concerns.

Keywords

• hoax news analysis
• national capital relocation
• support vector machine
• random forest