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primary topic: Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9)

Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9)
type: AcademicArticle
type: Article
abstract: This research aims to analyze user sentiment towards the ShopeePay application using the Naïve Bayes and SVM algorithms with data obtained through web scraping. Of the 1500 data obtained through scraping, 63 empty data were removed in the cleaning process, leaving 1437 data. This data was then divided into a training set (1149 data) and a test set (288 data). The results showed that the Naïve Bayes algorithm achieved an accuracy of 84.38%, a precision of 79.73%, a recall of 88.72%, and an F1-score of 83.99%, while the Support Vector Machine (SVM) algorithm achieved an accuracy of 80.56%, a precision of 84.07%, a recall of 71.43%, and an F1-score of 77.24%. Overall, Naïve Bayes performed better than Support Vector Machine, especially Naïve Bayes was superior in detecting positive sentiment, while SVM was better in detecting negative sentiment. Data visualization shows that out of 1437 users, around 52.7% gave positive reviews and 47.3% negative reviews, with a diverse rating distribution from users. Based on this distribution, the ShopeePay application user experience can be categorized as predominantly positive, with a difference of 5.4% indicating the difference between 52.7% positive reviews and 47.3% negative reviews from ShopeePay application users.
date: 2024-12-27
volume: 9
issue: 2024
is part of: Proceeding of TEKNOKA National Seminar - 9
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository
has document: Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9) (Text)
subject: T Technology (General)

Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9) (Text)
type: Document
has file: 01. Cover.pdf
has part: 01. Cover.pdf

Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9) (Text)
type: Document
has file: 04. Artikel.pdf
has part: 04. Artikel.pdf

Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9) (Text)
type: Document
has file: 03. Daftar Isi.pdf
has part: 03. Daftar Isi.pdf

Fakultas Teknologi Industri dan Informatika UHAMKA
type: Organization

Proceeding of TEKNOKA National Seminar - 9
type: Collection
issn: 25028782

Firman Noor Hasan
type: Person
given name: Firman Noor
family name: Hasan

HTML Summary of #44365 Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9)
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primary topic: Prosiding - Hilmi, Fadli, M.Rifansyah, Firman (Teknoka 9)

T Technology (General)
type: Concept