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: Identifikasi Tumbuhan Obat Berbasis Fraktal Menggunakan Clustering Fuzzy C-Means.
Abstrak: Identification medicinal plant species automatically still be a problem for recognizing various kind of medicinal plants in Indonesia. The research purpose is to develop medicinal plant identification system by using fractal and Fuzzy C-Means (FCM) clustering. Fractal method is used to extract image feture of the medicinal plant leaf. Beides, FCM clustering is needed to classify image feature medicinal plant into some lass or cluster. Two fractal approach used in this research are fractal dimension and fractal code. Fractal dimension is based on similiarity of the medicinal plant leaf image pattern and counted with box counting method, however fractal code is based on similiarity of the medicinal plant leaf image texture. This research used the data from the collection in Biofarmaka IPB plantation and glasshouse of Ex-Situ conservation of Indoensia Tropicana. 600 data is used contain of 20 variety of medicinal plants for each 30 sampel. This experimental result shows that 85.04% of FCM clustering based on dimension and 79.94% FCM clustering based on the fractal code. According to this result, medicinal plant identification system which are easy and with high accuracy will motivate public to empower and use medicinal plant in Indonesia which will increase Indonesian public health and wealth.
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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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