Judul: Ekstraksi Daun Menggunakan Dimensi Fraktal untuk Identifikasi Tumbuhan Obat di Indonesia
Abstrak: Identification medicinal plant species automatically still be a problem for recognizing various kind of medicinal plants in Indonesia. This research proposes a method for identifying a medicinal plant using Fractal Dimension and Probabilistic Neural Network (PNN). Fractal geometry offers an approach for the extraction of image which has the advantages in describing natural objects like leaves of medicinal plants. This is different from Euclidean geometry approaches that have been used to measure regular and symmetrical objects while the objects around us have an irregular shape. In this research, fractal dimension measured by Box Counting method. Fractal dimension has non-integer value that represent the self similarity of fractal. Identification results using Probabilistic Neural Network produces an accuracy of 67% and the results with showing the three classes that have the highest probability has the accuracy of 86.19%. Hence, the propose system is promising for medicinal plants identification in Indonesia.
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Judul: Penggabungan Dimensi Fraktal dan Kode Fraktal untuk Identifikasi Tumbuhan Obat Indonesia Menggunakan Probabilistic Neural Network
Abstrak: This research proposed a new method to identify Indonesia medicinal plants using fractal dimension (FD) and fractal code (FC) using Probabilistic Neural Network (PNN). This research investigates the effectiveness of fusion of FD and FC in order to identify Indonesia medicinal plants. FD is measured by Box Counting method. FD has non-integer value that represents the self-similarity of fractal. FC is based on the self-similarity in a picture. It means that small pieces of the picture can be approximated by transformed versions of some other (larger) pieces of the picture. The fusion of FD and FC is done by using vector fusion and Product Decision Rule (PDR). The total medicinal plants used in this research are 20 species taken from Biofarmaka Farm, Cikabayan and Green House Center Ex-Situ Conservation of Medicinal Plants Indonesia Tropical Forest. Each species consists of 30 images, thus the total images used in this research are 600 images. The PNN is trained using 450 images to classify 20 kinds of plants. The experimental results shows that fractal dimension has an accuracy rate of 57%, fractal code 21%, vector fusion 58%, and PDR 58%. The experimental result also shows that fractal fusion is not necessary because the fractal dimension has significant information compared to the fractal code.
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Judul: Sarcosporidiasis in slaughter animals
Abstrak: Sarcocystis which belong to the generally occuring parasites for they are found almost all over the countries of the world. Infection of Sarcocystis usually throught inges- tion of feces or flesh of infected animals. The pathogenesis of Sarcosporidiasis is considered as benign but when the Sarcocystis die in a host, sarcocystin or sarcosporidin is liberated thereby which lead to condemnation of meat in the abattoir. Besides condemnation of meat, Sarcocystis also causes: loss of appetite, anemia, lameness, weakness in the lion, diarrhea, fever, pyrexia, paralysis, emaciation, neuro logical disturbances, etc. " Amprolium "at the rate of 100 mg/Kg body weight per day has been practiced for prevention or to minimize Sarco- sporidiasis. Treatment must be started during incubation period. Shedding of Sarcocystis sporocysts in the feces of carnivores is the key factor in the spread of Sarcocystis infection. Therefore, control efforts must be based primarily on measures designed to break the cycle of Sarcocystis.
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