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.
Keyword: 

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.
Keyword: 

Judul: Enteric Collibacillosis Pada Anak Babi Baru Lahir: Patogenesa dan Perubahan-Perubahan Patologisnya
Abstrak: Diare disebabkan oleh infeksi bakteri Escherichia coli pada anak-anak babi baru lahir yang peka terhadap en terotoksin produk bakteri tersebut. Dikenal sebagai colibacillosis. Patogenesa dari colibacillosis anak babi baru lahir adalah (1) infeksi oleh E. coli patogen, (2) proliferasi E. coli di lumen usus halus, (3) produksi dan pelepasan enterotoksin, dan (4) aktifitas toksin pada usus halus. Dalam proses proliferasi, adanya antigen pili K88 sangat penting karena memungkinkan bakteri perlekatan dengan epitel mucosa usus halus. mengadakan Setelah ko lonisasi dan proliferasi segera toksin dilepaskan. Akti- fitas toksin menginduksi sekresi yang berlebihan dari u- sus sehingga banyak cairan yang dikeluarkan ke lumen usus. Hal ini mengakibatkan banyak cairan dan elektrolit hilang sehingga timbul diare, dehidrasi dan asidosis yang sering menyebabkan kematian. Perubahan-perubahan patologis yang umum adalah dis tensi usus halus, dilatasi lambung dan infark pada kurva- tura mayor. Perubahan-perubahan histologis yang terjadi adalah enteritis hemorrhagica acuta, oedem dan kongesti pembuluh darah di lamina propria, akumulassi leukosit inti polimorf, sel monosit, dan inti sel mengalami piknosis Thrombus pada vena dan degenerasi serta desquamasi sel epitel usus….
Keyword: