SENTIMENT ANALYSIS OF SHOPEE E-COMMERCE PRODUCT REVIEWS USING MOBILE-BASED NAÏVE BAYES CLASSIFIER METHOD

ANISAH, SITI (2025) SENTIMENT ANALYSIS OF SHOPEE E-COMMERCE PRODUCT REVIEWS USING MOBILE-BASED NAÏVE BAYES CLASSIFIER METHOD. Tugas Akhir thesis, Informatics.

[img] Text
5210411044_SITI ANISAH_ABSTRAK.pdf
Download (65kB)

Abstract

Product reviews significantly influence producers and consumers, as they serve as a valuable source of information regarding product quality. Manually processing large volumes of data for each product on Shopee—an online shopping platform—can be time-consuming and inefficient. Therefore, a sentiment analysis system is essential for extracting key information and objectively assessing product quality while handling extensive text data. The sentiment analysis process consists of several stages: crawling, preprocessing, word weighting, and sentiment classification. The objective of this study is to evaluate the sentiment analysis of customer reviews on Shopee using the Naïve Bayes method, which will classify sentiments as positive, negative, or neutral based on customers’ experiences with products and services. Consequently, customers can utilize e-commerce reviews as a basis for their purchasing decisions by determining whether they are favorable or unfavorable. Keywords: Sentiment Analysis, e-commerce, Naïve Bayes, Review, Shopee

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 09 May 2025 06:46
Last Modified: 09 May 2025 06:46
URI: http://eprints.uty.ac.id/id/eprint/17992

Actions (login required)

View Item View Item
UTY Open Access is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.