eprintid: 52288
rev_number: 26
eprint_status: archive
userid: 1636
dir: disk0/00/05/22/88
datestamp: 2026-04-20 00:45:13
lastmod: 2026-04-20 00:45:13
status_changed: 2026-04-20 00:45:13
type: article
metadata_visibility: show
creators_name: Hasan, Firman Noor
creators_id: firman.noorhasan@uhamka.ac.id
creators_orcid: 0000-0002-1246-3462
title: (JUTIF - S2) - Winanta, Hana, Hasan  [2026-04-19]
ispublished: pub
subjects: T1
divisions: 55201
abstract: The rapid growth of e-commerce platforms in Indonesia has generated a massive volume of product reviews, making sentiment classification essential for understanding customer perceptions and supporting data-driven decision making. This study aims to develop a sentiment classification model for Indonesia e-commerce product reviews while enhancing model transparency through Explainable Artificial Intelligence (XAI). The proposed approach employs a Random Forest classifier eith Term Frequency-Inverse Document Frequency (TF-IDF) for feature extraction. The dataset consists of 23,194 product reviews from the fashion and electronics categories, classified into positive, negative, and neutral sentiment. Model performance is evaluated using accuracy, precision, recall, and F1-Score metrics. Experimental results show taht the Random Forest model achieves an accuracy of 93.74%, with the best performance observed in the postive sentiment class. To improve interpretability, three XAI methods-LIME, SHAP, and ELI5-are applied. The analysis indicates that LIME is effective for local explanations, SHAP provides consistent global and local feature importence, and ELI5 offers concise and computationally efficient global explanations. This study contributes to the field of computer science by demostrating how comparative XAI analysis can bridge the gap between high-performing black-box models and interpretable sentiment classification in high-dimensional extual data, thereby supporting transparent and accountavle AI system in e-commerce applications.
date: 2026-04-19
date_type: published
publisher: Informatics, Universitas Jenderal Soedirman
official_url: https://jutif.if.unsoed.ac.id/index.php/jurnal/article/view/5642
id_number: https://doi.org/10.52436/1.jutif.2026.7.2.5642
full_text_status: public
publication: JUTIF: Jurnal Teknik Informatika
volume: 7
number: 2
pagerange: 1778-1799
refereed: TRUE
issn: 2723-3871
related_url_url: https://jutif.if.unsoed.ac.id/index.php/jurnal/index
related_url_type: pub
citation:   Hasan, Firman Noor  (2026) (JUTIF - S2) - Winanta, Hana, Hasan [2026-04-19].  JUTIF: Jurnal Teknik Informatika, 7 (2).  pp. 1778-1799.  ISSN 2723-3871     
document_url: http://repository.uhamka.ac.id/id/eprint/52288/10/%5B2026-04-19%5D%20-%20Winanta%2C%20Hana%2C%20Hasan%20%20%28JUTIF%20-%20S2%29.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/1/1.%20%20Cover.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/2/2.%20%20Editorial%20Team.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/3/3.%20%20Daftar%20Isi.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/4/4.%20%20Artikel.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/5/5.%20%20Turnitin%20-%20Similiarity%20Report%20%289%25%29.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/6/6.%20%20LOA%20-%20Winata%2C%20Hasan.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/7/Korespondensi.1%20-%20Submission%20Acknowledgement.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/8/Korespondensi.2%20-%20Editor%20Decision%20for%20Revision%20-%201.pdf
document_url: http://repository.uhamka.ac.id/id/eprint/52288/9/Korespondensi.3%20-%20Screenshot.pdf