Penerapan AI Agent Berbasis n8n untuk Otomatisasi Operasional Pertanian - Muhammad Rofiif Taqiyyuddin Nabiil; Hario Jati Setyadi; Akhmad Irsyad (METIK Jurnal, 2026)
This study aims to develop an artificial intelligence–based agricultural automation system by integrating an AI Agent with the n8n workflow automation platform. The development addresses common challenges in agricultural operations that remain manual, such as recording daily activities, scheduling reminders for fertilization and harvesting, and limited access to real-time weather information. The system was developed using the Waterfall model, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The proposed system integrates several components, including WhatsApp as the main user interface, n8n as the workflow controller, WAHA as the communication bridge, Google Sheets as the digital database, and an AI Agent for user query processing and recommendation generation. The Black Box Testing results show that all core functions operate as expected, covering activity recording, automatic reminders, recommendation delivery, and weekly report generation. The User Acceptance Test achieved a satisfaction score of 85 percent, categorized as very good, indicating that the system is user-friendly, responsive, and beneficial for improving agricultural efficiency. This research contributes to the advancement of AI-based information systems in the agricultural sector and demonstrates that integrating an AI Agent with n8n is an effective solution for supporting agricultural digitalization and implementing smart farming at the village level.