Building of Informatics, Technology and Science
Vol 6 No 3 (2024): December 2024

Analisis Sentimen Tanggapan Publik di Twitter Terkait Program Kerja Makan Siang Gratis Prabowo–Gibran Menggunakan Algoritma Naïve Bayes Classifier dan Support Vector Machine

Ramadhani, Annisa (Unknown)
Permana, Inggih (Unknown)
Afdal, M (Unknown)
Fronita, Mona (Unknown)



Article Info

Publish Date
03 Dec 2024

Abstract

Indonesia faces a serious challenge related to stunting, with rates reaching 21% in 2024, although this represents a decrease from 24% in 2021. In response, the government has launched various programs to address this issue, including nutrition education, health check-ups for pregnant women, and supplementary food provisions. Amid these efforts, the proposed free lunch program aims to improve nutritional quality for children and pregnant women. However, this program has sparked controversy over the required budget, estimated at IDR 450 trillion, which could impact the national budget balance and lead to inflation.This study analyzes public sentiment toward the free lunch program using the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms. An analysis of 1,028 tweets revealed that negative sentiment predominates at 44.84%, followed by positive sentiment (32.39%) and neutral sentiment (22.76%). SVM outperformed NBC with an accuracy of 75.39%, compared to NBC's 68.97%. The findings provide important insights into public perceptions of the program and highlight the need for further research to improve sentiment analysis methodologies.

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Journal Info

Abbrev

bits

Publisher

Subject

Computer Science & IT

Description

Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. ...