eprintid: 48664
rev_number: 30
eprint_status: archive
userid: 1636
dir: disk0/00/04/86/64
datestamp: 2026-01-27 01:27:10
lastmod: 2026-01-27 01:27:10
status_changed: 2026-01-27 01:27:10
type: article
metadata_visibility: show
creators_name: Hasan, Firman Noor
creators_id: firman.noorhasan@uhamka.ac.id
creators_orcid: 0000-0002-1246-3462
title: (IJID - S3) - Fathurrohman, Afandi, Wahyuningtyas, Nugroho, Hasan [2025-01-08]
ispublished: pub
subjects: T1
divisions: 55201
abstract: This study examines user sentiment towards Shopee Xpress delivery times using machine learning techniques. We collected 497 reviews from platforms like X and the Google Play Store, leveraging the valuable feedback despite its unstructured and informal nature. After labelling 398 reviews for model training and reserving 99 for sentiment prediction, we implemented two classification algorithms: Support Vector Machine (SVM) and Logistic Regression. These models categorised sentiments into negative, neutral, and positive classes. Despite class imbalance in the training data, SVM outperformed Logistic Regression with an accuracy of 93%, demonstrating a more balanced performance across sentiment categories compared to Logistic Regression's 90% accuracy. Both models showed consistent sentiment prediction on new data. Our findings highlight the potential of sentiment analysis as a valuable tool for Shopee Xpress to understand customer perceptions and improve delivery experiences. By providing actionable insights, this study can inform logistics improvements and enhance customer satisfaction. Future research could benefit from collaborating with Shopee to access internal data and integrating additional data sources for more comprehensive insights, ultimately driving business growth and customer loyalty. This study contributes to the growing body of research on sentiment analysis in logistics and e-commerce.
date: 2026-01-08
date_type: published
publisher: Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta
official_url: https://ejournal.uin-suka.ac.id/saintek/ijid/article/view/5073
id_number: https://doi.org/10.14421/ijid.2025.5073
full_text_status: public
publication: Sentiment Analysis on Shopee Xpress Delivery Time Reviews Using Support Vector Machine and Logistic Regression
volume: 14
number: 2
pagerange: 640-658
refereed: TRUE
issn: 2549-7448
related_url_url: https://ejournal.uin-suka.ac.id/saintek/ijid/index
related_url_type: pub
citation:   Hasan, Firman Noor  (2026) (IJID - S3) - Fathurrohman, Afandi, Wahyuningtyas, Nugroho, Hasan [2025-01-08].  Sentiment Analysis on Shopee Xpress Delivery Time Reviews Using Support Vector Machine and Logistic Regression, 14 (2).  pp. 640-658.  ISSN 2549-7448     
document_url: http://repository.uhamka.ac.id/id/eprint/48664/6/%5B2026-01-08%5D%20-%20Fathurrohman%2C%20Afandi%2C%20Wahyuningtyas%2C%20Nugroho%2C%20Hasan%20%20%28IJID-S3%29.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/48664/1/1.%20%20Cover.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/48664/2/2.%20%20Editorial%20Team.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/48664/3/3.%20%20Daftar%20Isi.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/48664/4/4.%20%20Artikel.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/48664/5/5.%20%20Turnitin%20-%20Similiarity%20Report%20%2810%25%29.pdf