APLIKASI JARINGAN SYARAF TIRUAN (JST) UNTUK PENDUGAAN SUHU LARUTAN NUTRISI YANG DISIRKULASIKAN DAN DIDINGINKAN SIANG-MALAM PADA TANAMAN TOMAT HIDROPONIK
Abstract: Cultivation of
tomato plant under hydroponics system in the greenhouse is suitable way to
improve fruit quality since it is easier to control environmental parameters.
In this system, water and nutrition are two important things for plant to
growth. In the tropical area such as Indonesia, air temperature is main
constraint in the plant production system. Increasing air temperature inside
the greenhouse has positive correlation to the raising temperature of nutrient
solution which affected to the ability of the plant to absord the nutrition.
The effective way to anticipate increasing of its temperature is by using the
cooling system of nutrient solution before circulated to the plant. This paper
presented the application of Articificial Neural Network (ANN) to estimate the
temperature of nutrient solution which was cooled on day-night time and
circulated to the plant. ANN models, called time delay neural network, consist
of 3 layers with 4 input nodes and 1 output node. As input model were t (time),
Tg(i) (air temperature inside the greenhouse on time i), Tt(i) (temperature of
nutrient solution in the tank on time i), Tb(i-1) (temperature of nutrient
solution in the plant plots on time i-1) and as output model was Tb(i)
(temperature of nutrient solution in the plant plots on time i). The model was
developed well with validation result better than heat transfer model
previously indicated by coefficient determination (R2) of 0.9498.
Penulis: Chusnul Arief,
Yohanes Aris Purwanto, Herry Suhardiyanto, Yudi Chadirin
Kode Jurnal: jppertaniandd100224