Penerapan Deep Learning untuk Analisis Sentimen Ulasan Produk dalam Memprediksi Perubahan Permintaan Pasar pada Platform E-Commerce
DOI:
https://doi.org/10.65310/v7bm9213Kata Kunci:
Deep Learning, Sentiment Analysis, Product Reviews, Market Demand Prediction, E-Commerce.Abstrak
High competition in the e-commerce sector demands superior user experience as the key to retention. The research adopts a quantitative approach, testing hypotheses using Structural Equation Modeling (SEM) on data from active platform users. The analysis confirms that Information System Quality significantly influences User Satisfaction, and Satisfaction exerts a strong influence on Customer Loyalty. The most crucial finding is the confirmation of partial mediation by User Satisfaction in transmitting the effect of Information System Quality to Loyalty. This highlights that technology investment must translate into a satisfying experience to effectively drive Loyalty. Managerial implications suggest the platform should prioritize optimizing usability and service responsiveness to bolster Satisfaction, which is the primary factor in maintaining a stable customer base.
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Referensi
Adrian, M. I., & Laksana, E. A. (2025). Optimalisasi Parameter Support Vector Machine dengan Algoritma PSO untuk Tugas Klasifikasi Sentimen Ulasan IMDb. Jurnal Algoritma, 22(1), 288-299. https://doi.org/10.33364/algoritma/v.22-1.2306.
Agustini, A., & Akib, A. (2025). Pemanfaatan Machine Learning Untuk Analisis Ulasan Pelanggan Dan Kinerja Penjualan Di Tokopedia. Akmen Jurnal Ilmiah, 22(1), 86-99. https://doi.org/10.37476/akmen.v22i1.5451.
Alam, W. Y., Junaidi, A., & Irnanda, Z. R. (2024). Peran Artificial Intelligence dalam Optimalisasi Customer Relationship Management (CRM) dan Pemasaran Digital. Economics and Digital Business Review, 5(2), 692-703.
Alfaridzi, D. D., Pudjiantoro, T. H., & Santikarama, I. (2025). Implementation of Aspect-Based Sentiment Analysis for Outdoor Gear Product Reviews on the Tokopedia E-Commerce Platform (Case Study: Eiger Adventure). Holistic Science, 5(2), 173-184. https://doi.org/10.56495/hs.v5i2.1230.
Apriana, D., & Yuliansyah, C. (2024). Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce). AL-MIKRAJ Jurnal Studi Islam Dan Humaniora (E-ISSN 2745-4584), 4(02), 514-527. https://doi.org/10.37680/almikraj.v4i02.4774.
Brightlocal. (2025). “Local Consumer Review Survey 2025”, tersedia di https://www.brightlocal.com/research/local-consumer-review-survey/, diakses pada 18 Desemeber 2025.
Deva Pratama, A. S., & Rijati, N. (2024). Pengenalan Emosi Ulasan Pelanggan E-Commerce Menggunakan Deep Learning Berbasis Transformer. Techno. com, 23(3). https://doi.org/10.62411/tc.v23i3.11090.
Fahnun, B. U., & Muhammad, S. A. S. (2025). Perbandingan Model Machine Learning Dalam Analisis Sentimen Ulasan Pengguna Aplikasi E-Commerce. Jurnal Ilmiah Teknologi dan Rekayasa, 30(1), 73-94. https://doi.org/10.35760/tr.2025.v30i1.13530.
Firanti, M. (2024). Penggunaan Algoritma Machine Learning dalam Prediksi Penjualan E-commerce. Circle Archive, 1(6).
Fuadi, W., & Afrillia, Y. (2025). Analisis Sentimen Review Aplikasi Stockbit Di Google Play Store Dan X (Twitter) Menggunakan Support Vector Machine: Sentiment Analysis Of Stockbit Application Reviews On Google Play Store And X (Twitter) Using Support Vector Machine. Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, 10(2), 1050-1062. https://doi.org/10.36341/rabit.v10i2.6446.
Harisatul, A., Saktia, A. D., & Adinta, S. T. (2023). Consumer Repurchase Intention Model In Lazada E-Commerce. Eksis: Jurnal Riset Ekonomi dan Bisnis, 18(2), 53-68. https://doi.org/10.26533/eksis.v18i2.1283.
Medium. (2025). “Consumer Sentiment Analysis 2025: Comprehensive Data from 10,000+ E-Commerce Stores”, tersedia di https://medium.com/%40robertrucker1190/consumer-sentiment-analysis-2025-comprehensive-data-from-10-000-e-commerce-stores-d0a83bb8f19e, diakses pada 18 Desember 2025.
Mubarok, D., Adjani, K., Hutama, B. D. R., Mutoffar, M. M., & Indrayani, R. (2025). Big Data Analytics dan Machine Learning untuk Memprediksi Perilaku Konsumen di E-commerce. Jurnal Informatika dan Rekayasa Elektronik, 8(1), 159-167. https://doi.org/10.36595/jire.v8i1.1561.
Nurjanah, S., & Apidana, Y. H. (2025). Analisis Sentimen TikTok untuk Mengevaluasi Reputasi Merek Pasca Kasus Overclaim: Studi pada Daviena Skincare. Technology and Informatics Insight Journal, 4(2), 74-91. https://doi.org/10.32639/h5x8te73.
Putri, C. A., Ginting, P., & Situmorang, S. H. (2021). E-service quality and relational marketing effect satisfaction with using mobile banking through user experience in Mandiri Syariah Bank KCP Medan Petisah. International journal of research and review, 8(06). https https://doi.org/10.47191/ijcsrr/V6-i10-17://doi.org/10.52403/ijrr.20210611.
Saputra, G. G., & Fadhilah, F. (2025). Peran Online Customer Experience Dalam Meningkatkan Customer Satisfaction Dan Repurchase Intention Pada Platform Digital. Ganaya: Jurnal Ilmu Sosial dan Humaniora, 8(2), 29-42. https://doi.org/10.37329/ganaya.v8i2.3950.
Setyawan, A. F., Ariyanto, A. D. P., Fikriah, F. K., & Nugraha, R. I. (2024). Analisis Sentimen Ulasan iPhone di Amazon Menggunakan Model Deep Learning BERT Berbasis Transformer. Elkom: Jurnal Elektronika dan Komputer, 17(2), 447-452. https://doi.org/10.51903/elkom.v17i2.2150.
Somad, A., & Majid, M. (2024). Kecerdasan Buatan Dalam Pemasaran: Tinjauan Sistematis Pemasaran Masa Depan. Jurnal Baruna Horizon, 7(2), 121-130. https://doi.org/10.52310/jbhorizon.v7i2.172.
Sondakh, D. E., Kom, S., Taju, S. W., Tene, M. G., & Pangaila, A. E. (2023). Sistem Analisis Sentimen Ulasan Aplikasi Belanja Online Menggunakan Metode Ensemble Learning. Cogito Smart Journal, 9(2), 280-291. https://doi.org/10.31154/cogito.v9i2.525.280-291.
Wafda, A. (2024). Integrasi Machine Learning dalam Ritel: Tinjauan Komprehensif tentang Prediksi Harga, Analisis Data Pelanggan, dan Pemanfaatan Media Sosial. Journal Artificial: Informatika dan Sistem Informasi, 2(2), 90-106. https://doi.org/10.54065/artificial.2.2.2024.543.
Wardani, S., Lubis, S. S., & Dewantoro, R. W. (2025). Analisis Big data untuk prediksi permintaan produk dalam E-commerce. Jurnal Penelitian Teknologi Informasi dan Sains, 3(1), 74-81. https://doi.org/10.54066/jptis.v3i1.3066.
Yessy Asri, S. T., Kuswardani, D., & Kom, M. (2024). Machine Learning & Deep Learning: Analisis Sentimen Menggunakan Ulasan Pengguna Aplikasi. Uwais Inspirasi indonesia..
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Hak Cipta (c) 2025 Harwati Harwati, Laili Afiatur Rosidah, Rika Rahmawati Milya (Author)
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