Sentiment Analysis of 'Free Lunch for Children' Policy on Social Media X Using Random Forest Algorithm

The concept of a welfare state emphasizes the main role of the government in providing protection and improving welfare such as health and education to its people. The free lunch program proposed by Prabowo Subianto and Gibran Rakabuming Raka aims to improve the nutritional quality of school children while driving the national economy. The public's reaction to Prabowo Subianto's work program plan, on free school lunch program and nutritional support for Indonesian students, is very diverse in perspective on X. The Random Forest algorithm proved to be quite effective in classifying public sentiment regarding the policy of “Free Lunch for Children.” With an overall accuracy of 73%, the model was able to categorize public opinion into positive, negative, and neutral categories. To improve the performance of the model, upsampling was performed to balance the classes in the dataset as well as hyperparameter tuning. After applying these techniques, the accuracy of the model increased significantly to 80%.

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Publication Details

Journal
Journal of Information Systems and Informatics
Published
2025-03-22
DOI
https://doi.org/10.51519/journalisi.v7i1.1039
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
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article

Sentiment Analysis of 'Free Lunch for Children' Policy on Social Media X Using Random Forest Algorithm

Muhammad Ikhsan
Journal of Information Systems and Informatics
Data Mining and Machine Learning Applications
article

Sentiment Analysis of 'Free Lunch for Children' Policy on Social Media X Using Random Forest Algorithm

Muhammad Ikhsan
article en

Abstract

The concept of a welfare state emphasizes the main role of the government in providing protection and improving welfare such as health and education to its people. The free lunch program proposed by Prabowo Subianto and Gibran Rakabuming Raka aims to improve the nutritional quality of school children while driving the national economy. The public's reaction to Prabowo Subianto's work program plan, on free school lunch program and nutritional support for Indonesian students, is very diverse in perspective on X. The Random Forest algorithm proved to be quite effective in classifying public sentiment regarding the policy of “Free Lunch for Children.” With an overall accuracy of 73%, the model was able to categorize public opinion into positive, negative, and neutral categories. To improve the performance of the model, upsampling was performed to balance the classes in the dataset as well as hyperparameter tuning. After applying these techniques, the accuracy of the model increased significantly to 80%.

Journal of Information Systems and InformaticsVol. 7(1)
Islamic University (BD)
Openalex Percentile: Top 90%
Data Mining and Machine Learning Applications
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