Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Exacta: Journal of Pure and Fundamental Research
Indra Setiawan
Universitas Mandiri Bina Prestasi

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Analysis of Public Sentiment Toward the Free Nutritious Meals Program Using the Naive Bayes Algorithm Afdal Perangin Angin; Indra Setiawan; Jeremia Revaldo Girsang; Aldo Jeremia Tumanggor; Andika Tioanta Ginting; Manuel Saputra Manalu; Desman Jaya Giawa
Exacta: Journal of Pure and Fundamental Research Vol. 1 No. 2 (2026): : June: Exacta: Journal of Pure and Fundamental Research
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/88fddw90

Abstract

The increasing use of digital platforms as spaces for expressing public opinion has created opportunities for applying natural language processing techniques to evaluate societal responses toward government policies. This study aims to analyze public sentiment toward the Program Makan Bergizi Gratis (MBG) using the Multinomial Naive Bayes algorithm. The research applies an empirical machine learning approach involving data preprocessing, lexicon-based sentiment labeling, feature extraction using Count Vectorizer with unigram and bigram representation, and model evaluation through accuracy, precision, recall, F1-score, and confusion matrix analysis. The dataset consists of 3,300 public comments processed through a structured computational pipeline and divided using stratified sampling into training and testing data. The findings indicate that public sentiment is dominated by negative responses, followed by neutral and positive categories, reflecting critical public evaluation toward program implementation aspects. The classification model demonstrates reliable performance in identifying sentiment patterns and provides an analytical framework for understanding digital public perception. This study contributes to computational social analysis by integrating machine learning techniques with policy-oriented sentiment monitoring.
Co-Authors Afdal Perangin Angin Aldo Jeremia Tumanggor Andika Tioanta Ginting Desman Jaya Giawa Jeremia Revaldo Girsang Manuel Saputra Manalu