(JTEKSIS - S4) - Saputra, Hasan [2024-07-01]

Hasan, Firman Noor (2024) (JTEKSIS - S4) - Saputra, Hasan [2024-07-01]. Sentiment Analysis on Free Lunch & Milk Program Using Naive Bayes Algorithm, 6 (3). pp. 411-419. ISSN 2655-8238

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Abstract

The utilization of social media platforms like Twitter has become crucial for the public to voice opinions regarding political programs, including the Free Lunch and Milk Program advocated by Presidential Candidate Pair number 02, Prabowo-Gibran, in the 2024 Presidential Election. This research employs the Naive Bayes classification method with the assistance of the RapidMiner application to analyze public sentiment towards the program. Out of the 785 Twitter data examined, approximately 81.7% displayed negative sentiment, while 6.6% were neutral, and 11.7% exhibited positive sentiment. Despite the prevalence of negative sentiment, there was also support for the program. Model evaluation utilizing 10-fold cross-validation, alongside SMOTEUP sampling and TF-IDF implementation, revealed an accuracy of 92.96%, recall of 85.30%, and precision of 94.57%. These results indicate that the model performs well in classifying sentiment from the test data.

Item Type:	Article
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Teknik Informatika
Depositing User:	Mr Firman Noor Hasan
Date Deposited:	08 Jul 2024 07:45
Last Modified:	08 Jul 2024 07:45
URI:	http://repository.uhamka.ac.id/id/eprint/35072

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