TINJAUAN LITERATUR ANALISIS SENTIMEN PRODUK E-COMMERCE: DATASET, PENDEKATAN, METODE, DAN PERFORMA

Malika Harsanto
Endah Sudarmilah


DOI: https://doi.org/10.29100/jipi.v10i3.8217

Abstract


Analisis sentimen terhadap ulasan produk e-commerce telah menjadi alat penting untuk memahami preferensi dan kepuasan pelanggan. Tinjauan literatur sistematis (SLR) ini mengevaluasi 78 penelitian dari tahun 2020 hingga 2024 untuk mengidentifikasi dataset, metode, dan perfor-ma dalam analisis sentimen produk e-commerce. Hasil penelitian menunjukkan bahwa metode hibrida, seperti Lexicon-BERT Compara-tive Framework dan Blockchain-LSTM Hybrid, mencatat akurasi tertinggi hingga 98,2%, sementara pendekatan berbasis logika fuzzy seperti Q-Rung Orthopair Fuzzy memiliki keterbatasan skalabilitas dengan akurasi terendah 0,74%. Dataset dari platform besar seperti Am-azon, Jingdong, dan Flipkart dominan digunakan, meskipun tantangan seperti inkonsistensi label dan ketidakseimbangan kelas masih menjadi hambatan. Rekomendasi untuk penelitian lanjutan mencakup pengem-bangan model hibrida yang menggabungkan NLP lanjutan dengan teknologi blockchain, teknik penanganan data tidak seimbang, serta integrasi data multimodal. Temuan ini menegaskan peran analisis sen-timen sebagai fondasi strategis untuk pengambilan keputusan bisnis, inovasi produk, dan peningkatan pengalaman pelanggan di era digital.

Keywords


Analisis sentimen, ulasan e-commerce; metode hibrida; tantangan dataset; integrasi data multimodal

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