Prediction Analysis of Nilapartava Lugens Distribution of Rice using Autonomous Drone Mapping Technology with Ground Sampling Area
Keywords:Autonomous Drone Mapping, Ground Sampling Area
The purpose of this study was to help farmers predict the spread of rice planthopper pests by utilizing Autonomous Drone Mapping technology with Ground Sampling Area. The object under study was rice farming land with an area of 64.5 m2 which often experienced disturbances in productivity and quality of rice. Autonomous Drone Mapping Technology with Ground Sampling Area integration. This technology is used to detect the spread of leafhoppers on agricultural land through mapping of the affected land through a map of conditions resulting from shooting and imagery produced by drones flown over agricultural land. This technology can help rice farmers to predict pest attack from an early age by handling and preventive measures so that the level of productivity and quality of rice is not compromised. Prediction analysis can take advantage of remote imaging photos from the use of Autonomous Drone Mapping with Ground Sampling Area by analyzing the spread prediction data with Tren Forecasting Prediction. Based on the analysis of the predictions from the photo of the spread of planthopper pests, the distribution formula is y = 25.396 ln(x) -34.948 with the maximum spread of leafhoppers occurring on the 49th day so that serious handling is needed by farmers..
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