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All Journal Jipmor: Jurnal Ilmu Pendidikan Dan Humaniora
Afrisa Fadilah
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Humanities Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Analisis Sentimen Pengguna Shopee Terhadap Fitur Cash On Delivery Menggunakan Metode Naive Bayes dan Visualisasi Data Dengan Python dan Power BI Afrisa Fadilah; Sri Wahyuni; Nadia Rista
Jipmor: Jurnal Ilmu Pendidikan Dan Humaniora Vol 3 No 2 (2025): December
Publisher : Institut Pendidikan Alfatah Mataram

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Abstract

This research discusses sentiment analysis of Shopee users towards the Cash on Delivery (COD) feature using the Naive Bayes Classifier method. COD is one of Shopee's most frequently used services but often generates pros and cons among users. The research data was obtained from a dataset of Shopee user reviews downloaded from Kaggle. The research stages include data collection, data preprocessing (cleaning, normalization, stopword removal, and sentiment labeling), application of the Naive Bayes algorithm, and visualization of the results using Power BI. The findings indicate that the Naive Bayes algorithm can classify sentiments with a good level of accuracy, while Power BI visualization helps to better understand the distribution and patterns of user sentiments. This research is expected to provide insights for Shopee in improving the quality of its COD service based on user perceptions.
Co-Authors Nadia Rista Sri Wahyuni