Judul: Pengelompokan citra tanda tangan menggunakan metode som kohonen dua dimensi dan praproses wavelet
Abstrak: Biometric is a science for recognizing the identity of a person based on their behavioral traits. A signature is one of the characteristics of human behavior. This research aims to cluster signature images using two dimension self organizing maps (SOM) Kohonen with and without wavelet transformation preprocessing. SOM Kohonen is a type of artificial neural network that has unsupervised learning method. The images used are 40x60 grayscale signature images. Image dimension is reduced to half of the image dimension using Haar Wavelet transform. Silhouette coefficient and Davies Bouldin Index (DBI) are used as the evaluation functions for the clustering. The result shows that optimum clustering for cluster images without Haar Wavelet transform is obtained when alpha is equal to 0.7, initial width neighbor equal to 4 and final width neighbor equal to 4. Optimum clustering for cluster images using Haar Wavelet transform is obtained when the value of DBI is minimum, which is achieved when the value of alpha is equal to 0.8, initial width neighbor equal to 4 and final width neighbor equal to 2
Keyword: 

Judul: Pengenalan Tanda Tangan dengan Citra Pelatihan Tunggal Menggunakan Algoritme VFI5 Berbasis Histogram
Abstrak: Biometrics is the science of establishing the identity of an individual based on the physical, chemical or behavioral attributes of the person. Signature is one of the most common object used in biometric system. In this research, we will use VFI5 algorithm to classify offline signature images. The classification method in this research is only using a single image as a training image. The feature used as the input for VFI5 algorithm is the gray level intensity of the image which represented as a histogram. Then, the histogram is divided into six types of interval. But before dividing the histogram, the images are partitioned into a few parts with fifteen different sizes. The result of this research indicates that images partitioned horizontally have better accuracy than images partitioned vertically. The highest accuracy in this research is 95.56% which is obtained using 15 x 10 pixels image partition. The result of this research also shows that the accuracy of the recognition is influenced by the size and the number of partition.
Keyword: 

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. ...
Keyword: