Implementasi Chatbot WhatsApp Berbasis NLP untuk Otomasi Pemesanan pada UMKM Perikanan dengan Hybrid BERT dan GPT
DOI:
https://doi.org/10.55606/juisik.v6i1.1973Keywords:
BERT, Chatbot, GPT, MySQL, NLPAbstract
Advances in information and communication technology have transformed the way micro, small, and medium enterprises interact with customers. Instant messaging platforms like WhatsApp have become a primary channel for customer service due to their massive adoption and ease of access. This article presents a WhatsApp-based chatbot designed to support product ordering processes in fishery SMEs. The chatbot was developed using a hybrid Natural Language Processing (NLP) approach, combining a fine‑tuned BERT model for structured intent classification and GPT‑4o Mini as a backup mechanism when the system encounters questions outside the trained scenarios. The system is integrated with a MySQL database to ensure that user interactions are automatically recorded and properly managed. The research methodology includes data collection, system design, implementation, and testing using the black-box testing method. The developed features are expected to provide relevant and natural responses while reducing administrative workload. The results show that the NLP-based chatbot successfully facilitates customer interactions and delivers product information quickly and accurately.
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