Sri Murdiawati
Universitas Teknokrat Indonesia

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Peran Machine Learning Dalam E-Commerce: Tinjauan Literatur Sistematis Terhadap Penerapan Dan Tantangan Sri Murdiawati; Amri Reza Wahyudin; Juan Adi Putra; Ryan Randy Suryono
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 9, No 2 (2026): Juli
Publisher : Institut Teknologi Gamalama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v9i2.448

Abstract

Abstrak: Perkembangan e-commerce menghasilkan banyak data yang besar dan rumit, sehingga membutuhkan teknologi canggih untuk membantu pengambilan keputusan dan meningkatkan pelayanan. Machine learning menjadi cara utama yang digunakan karena kemampuannya untuk mempelajari pola perilaku pengguna dan transaksi secara otomatis. Penelitian ini menganalisis penerapan machine learning dalam e-commerce dengan menggunakan metode Systematic Literature Review (SLR) terhadap 20 artikel jurnal dari dalam dan luar negeri. Kebaruan penelitian ini terletak pada sistesis yang menggabungkan berbagai aspek seperti bidang penerapan, metode algoritma, cara mengukur kinerja, tantangan teknis, serta dampak bisnis dalam satu kerangka analisis yang terstruktur. Hasil penelitian menunjukkan bahwa machine learning memiliki peran penting dalam sistem rekomendasi, analisis sentimen, mendeteksi penipuan, serta memprediksi penjualan, meskipun masih menghadapi tantangan seperti kualitas data, kebutuhan komputasi yang besar, dan kemampuan menjelaskan hasil.Kata Kunci: e-commerce; machine learning; systematic literature review; sistem rekomendasi.Abstract: The development of e-commerce has generated large amounts of complex data, requiring advanced technology to aid decision-making and improve services. Machine learning has become the primary method used due to its ability to automatically learn patterns of user behavior and transactions. This study analyzes the application of machine learning in e-commerce using the Systematic Literature Review (SLR) method on 20 journal articles from within and outside the country. The novelty of this research lies in its synthesis, which combines various aspects such as fields of application, algorithm methods, performance measurement methods, technical challenges, and business impacts into a single structured analytical framework. The results show that machine learning plays an important role in recommendation systems, sentiment analysis, fraud detection, and sales prediction, despite still facing challenges such as data quality, large computational requirements, and the ability to explain results.Keywords: e-commerce; machine learning; systematic literature review; recommendation system