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Tamrin .
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Journal : Jurnal Keteknikan Pertanian

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A Model of Vegetative Stage of Baby Cucumber Using Artificial Neural Network Tamrin .; K. B. Seminar; H. Suhardiyanto; S. Hardjoamidjojo
Jurnal Keteknikan Pertanian Vol. 19 No. 1 (2005): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.019.1.%p

Abstract

A model of how plant reacts to their micro climate is of great importance to control the physical micro climate around the plant and to other major input problems (such as rutinition intake). Artificial Neural Network (ANN) can be utilized to model a plant reaction to their microclimate in a more objective facshion by applying the ANN to measured data, and not from a pre-assumed model structure. This paper discusses a model of the plant response (the ratio of canopy area-stem diameter of baby cucumber) and the loss of nutrition solution as output and nutrition solution intake and microclimate (temperature, humidity, and irradiation) as input by using artificial neural network of dynamic response.
Optimization of Vegetative Stage of Baby Cucumber (Cucumis sativus L. Var. Marta) using the Genetic Algorithm Tamrin .; K. B. Seminar; H. Suhardiyanto; S. Hardjoamidjojo
Jurnal Keteknikan Pertanian Vol. 19 No. 3 (2005): Buletin Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.019.3.%p

Abstract

An  optimization was conducted to a growth model for baby cucumber (Cucumis sativus L. Var. Marta). The model gives information of nutrient intake and micro climate conditions (temperature, humidity, and irrediation) to get response of the plant (ratio of canopy area and stem diameter) and the loss of nutrient solution. The model ws then coupled with genetic algoritm in order to get optimum result efficiently. Two fitness functions were used in the application og genetic algoritm. The result showed that the first fitness function could be used to optimize the plant response (ratio of canopy area and stem diameter) and the loss of nutrient solution efficiently as indicated by the maximum fitness value (Pc = 0.6 and Pm = 0.01).
Penentuan Parameter Optimal Kendali Greenhouse Berbasis Fazi Dan Pid Menggunakan Algoritma Genetika Tamrin .
Jurnal Keteknikan Pertanian Vol. 22 No. 2 (2008): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.022.2.%p

Abstract

The development of the control system of adaptive biological-environment was equipped with the optimization technique of'Genetic Algorithm in solving the problem of optimizing parameters. Optimizing the determination ofparameters of fuzzy control and PID were carried out by stimulating the real noise from solar irradiation in greenhouse, such as fluctuation of solar radiation in day time. The parameters of optimal control were determined by minimizing the cumulative square error for each physical unit, such as temperature and humidity with the fitness function which was reciprocally arranged. The performance ofcontrol system was better with the availability ofgenetic algorithm, and therefore the mode of fuzzy control and PID could be used to control the whole biological-environment. The fuzzy parameters for temperatures were P1=O. 17, P2=O.32, P3=11.28, P4=4.58, and P5=141.89, for humidity P1=O.38, P2=O.05, P3 =6.96, P4 =11.73, and P5=968.65; whereas the PID parameter for temperature were Kp=O.06, TD=O.08, and TD=1.91, for humidity were Kp=O.01, TD=O.0012, and TD=16.Keywords: optimal parameter, fuzzy control, PIO control, genetic algorithmDiterima: 21 Januari 2008; Disetujui: 27 Mei 2008  
Co-Authors . MUSTARI H. Suhardiyanto K. B. Seminar S. Hardjoamidjojo