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Development of Irrigation System and Nutrition Prediction Model with ANFIS Method for Chili Plants

Arjon Turnip, Poltak Sihombing, Betty N. Fitriatin, Tualar Simarmata, George Michael Tampubolon, Tien Turmuktini, Endra Joelianto

Abstract



Irrigation systems in agriculture are one of the largest consumers of water in the world, and have been increasing due to growing population. The development of advanced irrigation technology based on modern techniques is necessary to ensure efficient use of water. Intelligent irrigation based on computer and vision technologies can assist in achieving optimal water utilization in agriculture by using highly available digital technology. This paper presents predictive modeling of irrigation needs for chili plants using the ANFIS method. This modeling uses input parameters in the form of soil moisture, plant age, planting temperature, and the daily requirement of water for plants. The daily fluid requirement parameters for plants can be found using conventional measurements (Gravimetry), these parameters will be the output parameters for the ANFIS modeling. This modeling is compared with reference measurements (conventional) resulting in a fairly proper accuracy of 90.7%. The proposed system is simple and affordable which makes the technology more precise.

Keywords


Agriculture, drip irrigation, chili plant, ANFIS, prediction, precision farming.

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