Analisis Sentimen Terhadap Bea Cukai Pada Media Sosial Twitter Menggunakan Metode Naive Bayes

Firdaus, Bayu (2024) Analisis Sentimen Terhadap Bea Cukai Pada Media Sosial Twitter Menggunakan Metode Naive Bayes. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

This research aims to analyze public sentiment towards customs duties on the social media platform Twitter using the Naïve Bayes method. Prompted by extensive discussions about customs duties in early 2023, this study explores public sentiment, Naïve Bayes classification, and classification performance evaluation. The benefit of this research is to provide insights to authorities to improve the quality of customs service and maintain a positive image among the public. With a dataset of 2622 tweets, consisting of 724 positive labels, 904 neutral labels, and 994 negative labels, the data indicates that public sentiment towards customs duties is mostly negative. The evaluation results show an accuracy of 82.44%, precision of 81.51%, recall of 70.52%, and an F1-Score of 75.03%. Through the implementation of a system using the Flask web framework, this research contributes to understanding public sentiment towards customs duties and provides input to enhance service quality and uphold the positive image of the institution. Consequently, it is hoped that the findings of this research can serve as a basis for more targeted and responsive policies to meet the needs and expectations of the public regarding customs services.

Item Type:

Thesis (Undergraduate)

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