The Role of Artificial Intelligence in Enhancing Business Intelligence Capabilities for E-Commerce Platforms

This research focuses on the application of BERT (Bidirectional Encoder Representations from Transformers) and Graph Neural Networks (GNNs) to improve business intelligence (BI) capabilities on e-commerce platforms. The main aim of the research is to develop automation methods for the classification of customer interactions and to create a more effective product recommendation system. In this study, BERT was used to analyze and classify customer interaction texts, including questions, complaints, and reviews, with accuracy reaching 97% and sentiment analysis accuracy of 93%. GNNs are applied to model complex relationships between customers and products based on transaction data, then used to provide product recommendations. The evaluation results show that the GNNs model achieved a mean average precision (MAP) of 0.92 and a normalized discounted cumulative gain (NDCG) of 0.88, indicating high relevance and accuracy in product recommendations. This research concludes that the integration of BERT and GNNs improves operational efficiency through classification automation but also provides added value in marketing strategies with better personalization of recommendations.

@article{Perangin-Angin2024,
  title     = {The Role of Artificial Intelligence in Enhancing Business Intelligence Capabilities for E-Commerce Platforms},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {9},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Sinek Mehuli Br Perangin-Angin and David Jumpa Malem Sembiring and Asprina Br Surbakti and Soleh Darmansyah},
  doi       = {10.14569/IJACSA.2024.0150941},
  url       = {https://doi.org/10.14569/IJACSA.2024.0150941}
}