Judul: Early warning system for supply crisis management of subsidized fertilizers distribution for rice farmers (Case Study in Banyumas, Central Java)
Abstrak: Fertilizer supply crisis in Indonesia occur almost every year. This crisis can be prevented by early detection before the crisis situation occurred. Preventive action would be much better than remedial action. In this research, an Artificial Neural Network (ANN) based decision support for supply crisis of subsidized fertilizer distribution was developed. The Early Warning detection was developed with backpropagation (BP) learning’s methods. The constructing of the data’s input for ANN based on the fundamental parameters of supply crisis of subsidized fertilizer by using Exponential Comparation Method (ECM) and expert’s judgments with Analytical Hierarchy Process (AHP), consisting of the critical factor causing supply crisis of subsidized fertilizer, so this system be able to assess of intensity of the crisis with more fast, effective and efficient.Based on the “trial and error” test of ANN’s training process, the best network performance for BP learning’s method was obtained. The best network performance for BP was showed by the Mean Square Error (MSE) score of 0.00000000531 (5.31.10-9) at the 38th epoch, when the system used sigmoid bipolar for hidden layer and linear’s activation function for output neuron, Levenberg-Marquadt’s algorithm training, the momentum score was 0.05, the learning rate score was 0.05, and the minimum error was 0.0000005 with the network architecture of [9 60 30 1], that is, 9 neurons in an input layer, 60 neurons in a first hidden layer, 30 neurons in a second hidden layer and 1 neuron in an output layer. The BP was trained with 66 actual data and tested with 15 actual data, with 87% accuracy rate. From the test shows that the network has been able to recognize patterns of crisis. To get the improved accuracy of detection it is recommended for additional training with the latest data.
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Judul: Pemodelan Decision Network untuk Menentukan Pola Tanam Pertanian Dinamis
Abstrak: Plants require different climatic conditions to grow well. The knowledge of optimum climate for plant to grow is essentially needed. The El Nino and La Nina phenomena affect the climate changes variability in Indonesia. El Nino causes a decrease in agricultural productivity due to the reduction in availability of water for crops. However, the La Nina phenomenon increases agricultural productivity due to the abundant availability of water. The strategy that can be done to solve the problem of climate change are to adjust the shape of cropping patterns and to forecast the season by using a Decision Network. Based on the Decision Network, the decision to select established cropping patterns is done using climate information and other obtained information before the decision is made. In this study, there are four information to be used. They are SOI index in August which can be used as an early possible indicator of rainy season changes, the length of rainy season, the rainfall in dry season, and the land area affected by drought. The objective of this research was to build the information model for agricultural cropping pattern by decision network. The data in this research were from 1965 to 2010. Cropping pattern can be used to produce a proper and accurate decision regarding to possibility of drought in areas. It also can be used to predict the possibility of loss amount that may arise. This study is conducted Indramayu District. The decisions are based on cropping patterns in Indramayu. The result showed that the model accuracy was 61.9% based on the relationship between the possibility of drought and drought data record in Indramayu from 1989 until 2009.
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Judul: Trichomonas Gallinae Penyebab Trichomonosis Pada Unggas
Abstrak: Trichomonas gallinae adalah protozoa yang bergerak aktof dengan keempat flagella yang mempunyai layar dan pada salah satu sisinya terdapat membran seperti sirip ikan yang berombak. Spesies dari genus Trichomonas ini mempunyai arti penting pada unggas, karena dapat menyebabkan infeksi pada alat pencernaan bagian atas.
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