Judul: Face Recognition Using VFI5 Algorithm with Wavelet Transformation.
Abstrak: Biometrik system is the introduction of the system to identify patterns that physiological characteristics a person with determining the autenticity of a specific psysiolagical and/or behavioral characteristic posessed by that person. Not all physiological characteristics can be used on the system biometrik, several characteristics that must be fulfilled that is universal, distinctiveness, permanent, and collectability. Face is one of the physiological characteristics that can not be falsified, therefore this research using biometrik face. Wavelet is an image processing method that can extraction features and the features that are important will not be lost when the image dimension reduction. Wavelet transformation of the image will be used as an input system in the face recognition of this research and mother wavelet used was the Haar wavelet. Method face recognition used of this research is the algorithm Voting Feature Interval (VFI5). VFI5 algorithm is an algorithm that represents the description of a concept by a set of interval values of the features or attributes. Phases of the training VFI5 algorithm produce the intervals, and each features a manner resulting image data represented by pixels on each element of data. Face image used in this research is measuring 92 × 112 pixels. The image of the face will have a wavelet transformation so that will be quarter of the original dimensions, the transformation level 1 produce image measure 46 × 56, the transformation level 2 produce image measure 23 × 28, and so on until level 6 produce image measure 2 × 2. In this research using training data 6 face images and testing data 4 face images. Rank accuracy the wavelet decomposition level increased from level 2 to level 6, different with level 1 if comparing level 2 is lower accuracy. In first level the accuracy is 72,5%, 90% for second level, 85% for third level, 80% for fourth level, 68% for fifth level, and 30% for sixth level. Keywords : image prosessing, face recognition, wavelet transformation, VFI5 algorithm.
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Judul: Signature Recognition using VFI5 Algorithm and Wavelet Preprocess.
Abstrak: Biometric is a science in recognizing the identity of a person based on their physical or behavioral traits. Today, one of the most widely applied biometric object is hand-written signature. In this research, we tried to identify offline handwritten signature using VFI5 (Voting Feature Intervals 5) classification algorithm. The VFI5 classification algorithm has been used previously on non-image objects with promising result. The feature used in the classification is the grayscale value of the image and the signature image dimension used in this research is 40×60 pixels which means originally there are 2400 features that relatively large to compute. Thus, Haar wavelet transform is used to reduce the dimension. This is done by taking only the approximation image of the transformation result, and leave the horizontal, vertical, diagonal details. The wavelet decomposition is applied until the fifth level, creating new low level images with 20×30, 10×15, 5×8, 3×4, 2×2 dimension respectively for the first, second, third, fourth, and fifth decomposition levels. The approximation images then classified using VFI5 algorithm, with 97.5%, 95%, 90%, 65%, and 62.5% accuracy respectively for the first, second, third, fourth, and fifth decomposition levels. It turned out that VFI5 algorithm can be used to identify images with wavelet transform to reduce the image dimension with good result, and the higher decomposition level applied, the more accuracy dropped. Keywords: signature identification, wavelet image dimension reduction, image classification, VFI5 algorithm.
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Judul: Koksidiosis Pada Usus Halus Kelinci Yang Disebabkan Oleh Eimeria magna
Abstrak: Penyakit yang disebabkan oleh infeksi protozoa dari genus Eimeria pada usus halus kelinci, disebut kok- sidiosis usus (Intestinal Coccidiosis). Salah satu jenis coccidia penyebabnya adalah E. magna. E. magna ini adalah parasit intraseluler, yang menyerang usus halus kelinci terutama bagian jejunum dan ileum. Dalam siklus hidupnya E. magna mengalami tiga tahap perkembangan, yaitu: 1. Skizogoni. Pada tahap ini terjadi pembentukan skizon, ukurannya berkisar antara 10-20 น. 2. Gametogoni. Pada tahap ini terjadi perkembangan seksual, terjadi lima hari setelah infeksi. 3. Sporogoni. Pada tahap ini terjadi pembentukan spora, bentuk ini dapat menginfeksi kelinci lainnya. Ookista yang bersporulasi dapat menginfeksi kelinci dalam suatu peternakan. Ookista ini berbentuk oval kadang kadang elips, panjangnya 28-42 u dan lebarnya 20-26 u. Apabila kelinci terinfeksi oleh ookista ini, dapat menurunkan berat badan terus menerus dan akhirnya menimbulkan kematian. Kelinci yang berumur muda lebih sering terserang penyakit ini dari pada kelinci dewasa, sehingga sering menyebabkan kerugian pada peternak. Gejala klinis yang terlihat tergantung dari banyaknya jumlah ookista yang termakan oleh kelinci. Kelinci muda sering terinfeksi oleh sejumlah besar ookista yang dapat menyebabkan kematian mendadak tanpa memperlihatkan gejala klinis terlebih dahulu. Pada infeksi akut terlihat gejala-gejala penurunan berat badan, dehidrasi, banyak minum, diare yang hebat dan sering menimbulkan kematian. ...
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