Implementing an AI Agent Chatbot to Improve Service Effectiveness in Mobile Phone Spare Parts and Service Stores

Authors

  • Futikhat Salsabila Universitas Amikom Purwokerto
  • Irfan Santiko Universitas Amikom Purwokerto

DOI:

https://doi.org/10.35671/jmtt.v4i1.88

Keywords:

Chatbot, , WhatsApp Business, , Artificial Intelligence, , n8n, , Services

Abstract

The development of digital technology encourages MSMEs to shift to automated service systems to increase efficiency. This study aims to develop a WhatsApp-based AI agent chatbot to improve the effectiveness of customer service at the Citra Karya Gemilang Store, especially in handling spare part stock information and cellphone service consultations. This study uses the Software Development Life Cycle (SDLC) Waterfall model with the stages of requirements analysis, system design, implementation, testing, and maintenance. The system was developed by integrating the WAHA API Gateway as a WhatsApp connector, n8n Workflow Automation as a conversation flow manager, Gemini AI as an artificial intelligence engine that understands message context, and Google Sheets as a dynamic database that stores product and service information in real-time. The implementation results show that the chatbot is able to provide a fast response 24 hours a day. Based on User Acceptance Testing (UAT) of 20 respondents, the system obtained a satisfaction level of 92% (Very Satisfied).

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Published

2025-04-30

How to Cite

[1]
F. Salsabila and I. Santiko, “Implementing an AI Agent Chatbot to Improve Service Effectiveness in Mobile Phone Spare Parts and Service Stores”, JMTT, vol. 4, no. 1, pp. 31–42, Apr. 2025.

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