Analisis Sentimen terhadap Jalan Rusak di Palembang Pada Media Sosial Menggunakan Algoritma Naïve Bayes
- Muhammad Rifqi Virgiansyah Universitas Multi Data Palembang, Kota Palembang, Indonesia
- Stephanie Stephanie Universitas Multi Data Palembang, Kota Palembang, Indonesia
-
Muhammad Rizky Pribadi
*
Universitas Multi Data Palembang, Kota Palembang,
Indonesia
(*) Corresponding Author
Abstract
In developed countries, the development of road infrastructure plays a vital role in driving economic development. The involvement of public authorities is very necessary in providing funds for infrastructure development, considering that roads are a very important form of public infrastructure. However, there are still some areas, such as Palembang, where damaged roads are still a serious problem. The Palembang regional government is suspected of being less proactive in improving road infrastructure in their area. In an effort to fight for the government's attention to road conditions in Palembang, the public uses social media as a means to voice complaints. A number of tweets, posts, and submissions using the keyword "Jalan Rusak Palembang" on Twitter, Instagram, and TikTok revealed that sentiment was found to be only 1.8% showing positive sentiment, 13.3% neutral sentiment, and 84.9% sentiment negativity towards damaged road conditions dominates. In order to collect further data regarding public perceptions of road conditions in Palembang, research was conducted using the Naïve Bayes algorithm. The test results show that the Naïve Bayes model provides an accuracy of 91,20, precision of 92,32%, recall of 91,20%, and F1 score of 91,26%, showing excellent performance in classifying public sentiment towards damaged roads in Palembang.
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