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Technology in agriculture is growing, one of them is hydroponic techniques because it uses an
Internet of Things (IoT) based system. One of the plants used in hydroponic techniques is the
pakcoy vegetable plant. Pakcoy is one of the vegetables that has the widest distribution in Asia.
In addition, the characteristics of pakcoy vegetables are almost the same as mustard greens.
Pakcoy vegetables are also easy to cultivate because they only require a small amount of land
and a short harvest period. This system is built using a microcontroller and computer vision
techniques as a control center and uses a Raspberry Pi 4 type B mini PC as a visual notification
and is equipped with a dc motor gearbox, L298N motor driver and webcam camera. This
system works automatically to control which plants are healthy and which plants are sick. This
study aims to detect diseased plants and healthy plants on pakcoy plants with a hydroponic
pakcoy plant monitoring tool that uses a microcontroller and computer vision techniques. This
tool works by taking pictures directly through a webcam camera, then processing them with a
trained model. The output of this tool displays the probability value of pakcoy plants showing
healthy plants and sick plants. From the results of testing the validation data using 60 validation
data, based on the accuracy of the detection tool healthy and sick plants were able to correctly
identify 38 validation data and 22 data were not recognized properly, so the accuracy of the
value was 63%. and produces an f1-score of 0,87
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