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ANFIS Implementation System Design on Environmental Control System for Optimizing the Growth of Robusta Coffee Seeds in the Greenhouse Denny Utomo; Mohammad Nor; Dalia Ahmed
Akiratech Vol. 3 No. 3 (2026)
Publisher : CV. Akira Java Bulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63935/akiratech.v3i3.281

Abstract

The growth of robusta coffee seedlings is greatly influenced by the stability of environmental conditions, especially temperature, air humidity, and soil pH. Dynamic tropical climate change and limitations of conventional control systems cause greenhouse environmental management to not run optimally. This study proposes the design of an Internet of Things (IoT)-based greenhouse environmental control system with the application of the Adaptive Neuro Fuzzy Inference System (ANFIS) method to support the optimization of the growth of robusta coffee seedlings. This system is able to monitor environmental parameters in real-time through IoT devices integrated with web applications. Environmental data is then processed using ANFIS as the basis for automatic actuator control decision-making to maintain the stability of environmental conditions according to the physiological needs of plants. The web application functions as a medium for data visualization, historical data analysis, and reporting on greenhouse environmental conditions.