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: 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: Pengaruh vaksin aktif dan inaktif terhadap kekebalan dalam pencegahan penyakit newcastle pada ayam
Abstrak: Penyakit Newcastle adalah penyakit yang bersifat infeksius dan kontagius yang menyerang unggas terutama ayam dan kalkun; menimbulkan kematian, penurunan produksi dan kwalitas telur sehingga menimbulkan kerugian ekonomi yang besar; disebabkan oleh paramyxovirus yang termasuk ke dalam golongan virus yang berinti asam ribonukleat. Virus penyebab penyakit ini terdiri atas beberapa galur yaitu velogenik, mesogenik dan lentogenik. Vaksinasi adalah salah satu cara untuk mencegah timbulnya penyakit dan kerugian yang ditimbulkannya. Vaksin terdiri atas vaksin aktif dan inaktif atau vaksin dalam emulsi minyak. Vaksinasi pada umur dini adalah cara yang paling baik dilakukan. Umur ayam yang tepat mulai dilaksanakan vaksinasi adalah pada umur 4 hari, karena pada saat ini titerantibodi asal induk sudah mulai turun dan kondisi ayam sudah mulai kuat untuk dilakukan vaksinasi jika melakukannya pada ayam umur sehari. ...
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