Penerapan Metode Perceptron untuk Otomatisasi Penyiraman Tahap Penyemaian pada Model Pertanian Vertikal
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Noprianto, Sigit Prasetyo
Siregar, Riki Ruli Affandi
Siregar, Riki Ruli Affandi
Subject
Teknik Informatika
Datestamp
2022-09-26 06:35:15
Abstract :
This research conducted to improving the watering process in seeding step on vertical agricultural which is still way conventional. The process of seed watering changed into automated by the watering machine based microcontroller Arduino Mega 2560. The watering process based on temperature condition, humidity and soil moisture which is obtained by the outcome of sensor reading DS18B20 for temperature value, DHT11 sensor for humidity value, and YL-69 sensor for soil moisture value. In this watering tool, the Perceptron algorithm is applied to determine the water pump status whether it should be activated or deactivated based on the values of temperature, humidity and soil moisture. The information of temperature, humidity and soil moisture can be monitored by the plant owner through web-based application. Based on the test result, by applying Perceptron Algorithm in this automatic watering tool, was obtained an accuracy value 87,5% with an error percentage value 12,5%.
This research conducted to improving the watering process in seeding step on vertical agricultural which is still way conventional. The process of seed watering changed into automated by the watering machine based microcontroller Arduino Mega 2560. The watering process based on temperature condition, humidity and soil moisture which is obtained by the outcome of sensor reading DS18B20 for temperature value, DHT11 sensor for humidity value, and YL-69 sensor for soil moisture value. In this watering tool, the Perceptron algorithm is applied to determine the water pump status whether it should be activated or deactivated based on the values of temperature, humidity and soil moisture. The information of temperature, humidity and soil moisture can be monitored by the plant owner through web-based application. Based on the test result, by applying Perceptron Algorithm in this automatic watering tool, was obtained an accuracy value 87,5% with an error percentage value 12,5%.
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