Repository UHAMKA(JUTIF - S2) - Winanta, Hana, Hasan [2026-04-19]Firman NoorHasanauthorThe 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.T Technology (General)2026-04-19Informatics, Universitas Jenderal SoedirmanArticle

For work being deposited by its own author: In self-archiving this collection of files and associated bibliographic metadata, I grant Repository UHAMKA the right to store them and to make them permanently available publicly for free on-line. I declare that this material is my own intellectual property and I understand that Repository UHAMKA does not assume any responsibility if there is any breach of copyright in distributing these files or metadata. (All authors are urged to prominently assert their copyright on the title page of their work.)

For work being deposited by someone other than its author: I hereby declare that the collection of files and associated bibliographic metadata that I am archiving at Repository UHAMKA) is in the public domain. If this is not the case, I accept full responsibility for any breach of copyright that distributing these files or metadata may entail.

Clicking on the deposit button indicates your agreement to these terms.