Sistem Pengontrolan Pengairan Budidaya Tanaman Tomat Berdasarkan Kelembaban Dan Suhu Tanah Berbasis Artificial Intelligence

Nida Nur Afifah, Porman Pangaribuan

Abstract

ABSTRAK
Pengairan pada tanaman tomat merupakan salah satu faktor penting dalam proses pertumbuhan dalam menjaga kesuburan.
Tetapi, pemberian air yang tidak sesuai akan membuat pertumbuhan tanaman tomat kurang optimal. Seperti tanaman busuk
ketika kurangnya pengairan dan terserangnya bakteri ketika pengairan berlebih. Untuk menyelesaikan permasalahan yang
ada, dibutuhkannya sistem pengairan tanaman tomat dengan melihat dari tingkat kelembaban dan suhu tanah tanaman.
Pada penelitian tugas akhir ini dirancang sebuah sistem untuk mengontrol pengairan yang diterapkan pada tanaman tomat
menggunakan sensor kelembaban tanah dan sensor suhu tanah dan arduino sebagai kontrol sistem. Melalui Artficial
Intelligence diharapkan bisa mengklasifikasikan nilai-nilai mana saja yang akan membuat pompa hidup untuk mengairi dan
membuat pompa mati agar berhenti mengairi dengan metode yang digunakan yaitu Artificial Neural Network. Untuk
mengukur kelembaban tanah sensor akan ditanam dalam tanah kemudian akan membaca kadar air. Kelembaban tanah yang
ideal untuk tanaman tomat berkisar 60-80%. Selain faktor Kelembaban, suhu tanah pada tanaman berpengaruh dalam proses
pertumbuhan. Sensor suhu tanah juga akan ditanam dalam tanah pada kedalaman 5 cm. Tanaman tomat berkembang pada
suhu 24-28°C.
Pada penelitian ini didapatkan bahwa sensor kelembaban tanah FC-28 dan sensor suhu DS18B20 waterproof mampu
mendeteksi kelembaban dan suhu tanah yang dibutuhkan sistem untuk mengairi tanaman tomat. Nilai kelembaban yang
terdeteksi untuk mengairi tanaman adalah < 60% sedangkan untuk suhu tanah adalah > 28°C. Dengan metode ANN yang
digunakan pada sistem memiliki akurasi sebesar 90%.
Kata Kunci: Tomat, Sensor Kelembaban Tanah FC-28, Sensor Suhu Tanah DS18B20 Waterproof, Pompa, Artificial
Neural Network.
ABSTRACT
Irrigation of tomato plants is an important factors in the process of plant growth in maintaining fertility. But, improper
water supply will make tomato plant growth less than optimal. Like rotten plants, when there is a lack of irrigation and
bacteria attack when they are over watering. Many automatic servoing gates have been made, it's just that it still has
shortcomings, including when there is rain and drought, then the servo that is flowed into a rice field or flowed to another
servoing because of the excess servo level in the rice field is still using the power of farmers to solve it. So farmers have to
check continuously into the fields.
To solve the existing problems, a tomato plant irrigation system is needed by looking at the level of soil moisture and soil
temperature of the plant. In this final project research designed a system to control irrigation applied to tomato plants using
a soil moisture sensor and a soil temperature sensor and Arduino as a control system. Through Artficial Intelligence, it is
expected to be able to classify which values will make the pump start to irrigate and make the pump stop to stop watering
with the method used, namely the Artificial Neural Network. To measure soil moisture the sensor will be planted in the soil
and then will read the moisture content. The ideal soil moisture for tomato plants ranges from 60-80%. In addition to the
humidity factor, soil temperature in plants has an effect on the growth process. The soil temperature sensor will also be
planted in the soil at a depth of 5 cm. Tomato plants thrive at 24-28 ° C.
In this study, it was found that the FC-28 soil moisture sensor and the DS18B20 waterproof temperature sensor were able
to detect the moisture and soil temperature needed by the system to irrigate tomato plants. The detected moisture value for
irrigating plants was <60% while for soil temperature was> 28 ° C. With the ANN method used in the system has an
accuracy of 90%.
Keywords: Tomato, FC-28 Soil Moisture Sensor, DS18B20 Waterproof Soil Temperature Sensor, Pump, Artificial
Intelligence, Artificial Neural Network.

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