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All Journal Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) INOVTEK Polbeng - Seri Informatika
Imran, Athallah Yasyfi
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Computer Science & IT Education Social Sciences

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Optimization of Sentiment Analysis on Tokopedia User Reviews Using Gridsearchcv and Smote with Machine Learning Algorithms Imran, Athallah Yasyfi; Sanjaya, M. Rudi; Bayu Wijaya Putra; Gabriel Ekoputra Hartono Cahyadi
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/5ax8km80

Abstract

Understanding user sentiment from e-commerce reviews is essential for platform improvement and business strategy. This study compares three machine learning algorithms—Logistic Regression, Random Forest, and XGBoost—for sentiment classification of Indonesian-language Tokopedia reviews. A dataset of 6,822 user reviews was preprocessed through tokenization, stopword removal, and TF-IDF vectorization. To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied to the training set. Models were evaluated using accuracy, precision, recall, and F1-score. Results demonstrate that Random Forest achieved the highest accuracy at 86.86%, followed by Logistic Regression at 84.86%, and XGBoost at 82.60%. The application of SMOTE significantly improved classification performance across all models, particularly for minority sentiment classes. These findings indicate that tree-based ensemble methods, especially Random Forest, are effective for sentiment analysis in imbalanced e-commerce datasets. This research provides practical insights for e-commerce platforms to implement automated sentiment monitoring systems, enabling faster response to customer feedback and targeted service improvements. However, the study is limited to Tokopedia reviews and may not generalize to other platforms or languages. Future work should explore deep learning approaches and cross-platform validation to enhance model robustness.
Penerapan artificial intelligence media desain website pembelajaran inovatif Sanjaya, M. Rudi; Ruskan, Endang Lestari; Indah, Dwi Rosa; Putra, Bayu Wijaya; Afif, Hasnan; Seprina, Iin; Faiq, Al Iksan; Wijayanto, Muhammad Ravi; Imran, Athallah Yasyfi; Danendra, Muhammad Archi Daffa; Rachmad, M. Ichsan Farel
Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Vol. 7 No. 1 (2026)
Publisher : Universitas Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jp2m.v7i1.24377

Abstract

Program Kreativitas Mahasiswa (PKM) ini bertujuan untuk meningkatkan kompetensi digital guru melalui penerapan teknologi Artificial Intelligence (AI) dalam desain website sekolah dan pengembangan media pembelajaran inovatif di SMA Negeri 10 Palembang.  Kegiatan ini dilatarbelakangi oleh kebutuhan guru untuk beradaptasi dengan era pembelajaran digital yang menuntut keahlian, kreativitas, efisiensi, dan interaktivitas tinggi. Metode pengabdian kepada masyarakat menggunakan pendampingan, pelatihan, praktik, diskusi. Melalui pelatihan berbasis praktik, guru dibimbing menggunakan AI dalam pembuatan desain website sekolah yang dinamis serta pengembangan media pembelajaran interaktif seperti pembuatan media pembelajaran aplikasi Gamma, ChatGPT, Wix Studio, Web Flow.  Hasil kegiatan di ukur dan di evauasi menggunakan test pre test dan post test dimana hasil tersebut menunjukkan peningkatan kemampuan guru dalam mengintegrasikan teknologi AI (ChatGPT, Gamma, Wix Studio, Web Flow) pada proses pembelajaran inovatif, kreatif, kolaboratif, dan berorientasi teknologi di  SMA Negeri 10 Palembang. sekolah SMA N 10 Palembang . Program ini berkontribusi nyata dalam mendorong transformasi digital pendidikan serta memperkuat peran guru di SMA Negeri 10 Palembang sebagai inovator dalam lingkungan belajar yang modern dan adaptif yang berbasis teknologi digital.
Co-Authors Afif, Hasnan Bayu Wijaya Putra Danendra, Muhammad Archi Daffa Dwi Rosa Indah Endang Lestari Ruskan Faiq, Al Iksan Gabriel Ekoputra Hartono Cahyadi Rachmad, M. Ichsan Farel Sanjaya, M. Rudi Seprina, Iin Wijayanto, Muhammad Ravi