Detecting Bot Comments on a Product in Shopee Using the Gradient Boosting Method
DOI:
https://doi.org/10.51967/tanesa.v26i1.3344Keywords:
Bot Comment Detection, Gradient Boosting, E-commerce, Shopee, Text ClassificationAbstract
Shopee is one of the largest e-commerce platforms in Southeast Asia, providing a product comment feature that serves as a primary reference for prospective buyers to assess product quality and seller reputation. Unfortunately, the prevalence of fake comments generated by bots—characterized by rigid language, repetitive patterns, and excessive praise—raises concerns about the authenticity of available reviews. This issue can negatively influence consumers’ purchasing decisions. This study aims to develop an automated system capable of detecting bot comments using the Gradient Boosting algorithm. A total of 3,000 comments were manually collected from various product categories and labeled directly by the researchers. The comment data were then processed through several stages, including text cleaning, tokenization, and lemmatization, to prepare for model analysis. The trained model demonstrated excellent performance, achieving an accuracy of 94.09%, precision of 95.99%, recall of 83.23%, and an F1-score of 89.13%. Based on these results, it can be concluded that the Gradient Boosting algorithm is highly effective in classifying bot comments and can help improve consumer trust and security in online shopping.
References
Dwiyansaputra, Ramaditia, Gibran Satya Nugraha, Fitri Bimantoro, and Arik Aranta. DETEKSI SMS SPAM BERBAHASA INDONESIA MENGGUNAKAN TF-IDF DAN STOCHASTIC GRADIENT DESCENT CLASSIFIER (Indonesian SMS Spam Detection Using TF-IDF and Stochastic Gradient Descent Classifier). http://jtika.if.unram.ac.id/index.php/JTIKA/.
Elsa Suryana, Silvia, and Budi Warsito. “PENERAPAN GRADIENT BOOSTING DENGAN HYPEROPT UNTUK MEMPREDIKSI KEBERHASILAN TELEMARKETING BANK.” 10: 617–23. https://ejournal3.undip.ac.id/index.php/gaussian/.
Gudiato, C, E Sediyono, and I Sembiring. 2022. “Analisis Sistem E-Commerce Pada Shopee Untuk Meningkatkan Daya Saing Menggunakan Metode S.W.O.T.” JIFOTECH (Journal of Information Technology) 2(1): 6–9. doi:10.46229/jifotech.v2i1.294.
Kurniawan, Hendra, and Maritim Raja Ali Haji Jl Politeknik Senggarang. 2020. “Jurnal Sustainable: Jurnal Hasil Penelitian Dan Industri Terapan Deteksi Twitter Bot Menggunakan Klasifikasi Decision Tree.” 09(01): 31–37.
Lestari, Tri Putri. 2022. “Analisis Text Mining Pada Sosial Media Twitter Menggunakan Metode Support Vector Machine (SVM) Dan Social Network Analysis (SNA).” Jurnal Informatika Ekonomi Bisnis: 65–71. doi:10.37034/infeb.v4i3.146.
Muktafin, E H, K Kusrini, and E T Luthfi. 2020. “Analisis Sentimen Pada Ulasan Pembelian Produk Di Marketplace Shopee Menggunakan Pendekatan Natural Language Processing.” Jurnal Eksplora Informatika 10(1): 32–42. doi:10.30864/eksplora.v10i1.390.
Muktafin, Elik Hari, Kusrini Kusrini, and Emha Taufiq Luthfi. 2020. “Analisis Sentimen Pada Ulasan Pembelian Produk Di Marketplace Shopee Menggunakan Pendekatan Natural Language Processing.” Jurnal Eksplora Informatika 10(1): 32–42. doi:10.30864/eksplora.v10i1.390.
Munawar, Zen, Herru Soerjono, Novianti Indah Putri, Hernawati, and Andina Dwijayanti. 2023. “Manfaat Kecerdasan Buatan ChatGPT Untuk Membantu Penulisan Ilmiah.” TEMATIK 10(1): 54–60. doi:10.38204/tematik.v10i1.1291.
Nurdin, Rizal, and Rizwan. 2019. 1 Jurnal Telematika Pendeteksian Dokumen Plagiarisme Dengan Menggunakan Metode Weight Tree.
Priyatno, A M, M M Muttaqi, F Syuhada, and A Z Arifin. 2019. “Deteksi Bot Spammer Twitter Berbasis Time Interval Entropy Dan Global Vectors for Word Representations Tweet’s Hashtag.” Register: Jurnal Ilmiah Teknologi Sistem Informasi 5(1): 37–46. doi:10.26594/register.v5i1.1382.
Puspitasari, Agreianti, Astrid Noviana Paradhita, Yohanes Wien Tineka, Vivin Sulistyowati, Ni Komang Septia Noriska, and Haryanto. 2024. “Natural Language Processing (NLP) Technology for Chatbot Website.” Jurnal Penelitian Pendidikan IPA 10(SpecialIssue): 319–24. doi:10.29303/jppipa.v10ispecialissue.8241.
Rayadin, M Amhar, M Musaruddin, and R Adi Saputra. 2024. “Implementasi Ensemble Learning Metode XGBoost Dan Random Forest Untuk Prediksi Waktu Penggantian Baterai Aki.” BIOS: Jurnal Teknologi Informasi Dan Rekayasa Komputer 5(2): 111–19. doi:10.37148/bios.v5i2.128.
Rayadin, Muhamad Amhar, Mustarum Musaruddin, Rizal Adi Saputra, and Isnawaty Isnawaty. 2024a. “Implementasi Ensemble Learning Metode XGBoost Dan Random Forest Untuk Prediksi Waktu Penggantian Baterai Aki.” BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer 5(2): 111–19. doi:10.37148/bios.v5i2.128.
Rayadin, Muhamad Amhar, Mustarum Musaruddin, Rizal Adi Saputra, and Isnawaty Isnawaty. 2024b. “Implementasi Ensemble Learning Metode XGBoost Dan Random Forest Untuk Prediksi Waktu Penggantian Baterai Aki.” BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer 5(2): 111–19. doi:10.37148/bios.v5i2.128.
Ridwansyah, Muhammad, and Hadi Zakaria. 2023. 1 JURIHUM : Jurnal Inovasi dan Humaniora Implementasi Algortima Gradient Boosting Pada Aplikasi Hutang Piutang Perorangan Secara Berbasis Web Untuk Meningkatan Akurasi Prediksi Pelunasan Hutang (Studi Kasus : PT Naila Kreasi Mandiri). https://jurnalmahasiswa.com/index.php/jurihum.
Rosnita, Lidya. 14 DENGAN OPTICAL CHARACTER RECOGNITION DI ORBIT FUTURE ACADEMY.
Rosnita, Lidya, Sujacka Retno, and Suhaiba Nasyira Hariono. 15 PENERAPAN SISTEM DETEKSI PENGISIAN RUANG PARKIR KENDARAAN RODA 4 MENGGUNAKAN METODE COMPUTER VISION DI ORBIT FUTURE ACADEMY.
Rusmarasy, Bestralaga, Bayu Priyambadha, and Fajar Pradana. 2019. 3 Pengembangan Chat Bot Pada CoMa Untuk Memberikan Motivasi Kepada Pengguna Menggunakan AIML. http://j-ptiik.ub.ac.id.
Urlamma, D., M. Supriya, D. Lavanya, and A. Hari Priya. 2024. “Detection Of Phishing Websites Using Gradient Boosting Classifier Based On URL.” IARJSET 11(3). doi:10.17148/iarjset.2024.11318.
Urlamma, D, M Supriya, D Lavanya, and A Hari Priya. 2024. “Detection Of Phishing Websites Using Gradient Boosting Classifier Based On URL.” International Advanced Research Journal in Science, Engineering and Technology 11(3): 116–21. doi:10.17148/iarjset.2024.11318.
Wijaya, Y F, S Yulianto, and J Prasetyo. 2021. “Model Penilaian Tata Guna Lahan Dengan Citra Landsat 8 OLI Menggunakan Algoritma XGBoost Diwilayah Beresiko Tsunami (Studi Kasus : Kota Palu Sulawesi Tengah).” Indonesia Journal of Computing Modeling 4(1): 24–28. doi:10.24246/icm.v4i1.4981.
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