Judul: Perbandingan SOM dan LVQ pada Identifikasi Citra Wajah dengan Wavelet sebagai Ekstraksi Ciri
Abstrak: Face recognition is one of challenging research topics in computer science because human face is difficult to be modelled. In this research, SOM and LVQ are proposed for frontal face recognition. The purpose is to compare LVQ and SOM based on identification accuracy. Training uses 400 images from 20 different individuals, and the dimension is 180 x 200 pixels. The data are retrieved from University of Essex, UK. Coefficient approximation at Haar wavelet level 6 is used as feature for classification and clustering process. K-fold cross validation with 10-fold is used to divide training and testing data. The experiment is divided into 3 sets, i.e., the experiment using SOM, LVQ, and LVQ initialized by SOM. The highest accuracy achieved by SOM is 97.8974%, while both LVQ and LVQ initialized by SOM achieve 100% accuracy. Based on the accuracy, LVQ proves to be better than SOM for frontal face recognition. This research needs to be improved in order to recognize various poses and changing expressions.
Keyword: Self Organizing Map (SOM), Learning Vector Quantization (LVQ), K-fold cross validation, Haar wavelet, frontal face recognition

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: Definisi zat besi ( Fe ) pada anak babi
Abstrak: Dalam bidang sub sektor peternakan, ternak babi mempunyai prospek yang cukup baik untuk dikembangkan dalam rangka meningkatkan eksport non migas. Namun anak-anak babi yang sedang menyusu sering mengalami defisiensi zat besi (Fe). Bila masalah ini tidak segera ditanggulangi, peternak akan mengalami kerugian. Zat besi dapat diperoleh dari makanan yang berasal dari hewan (tepung tulang, tepung ikan, tepung daging, "skimmed milk"); tumbuh-tumbuhan (leguminosae, rumput-rumputan, biji-bijian) dan mineral alam (Girindra, 1979). Dalam tubuh hewan, zat besi berperanan sebagai pembawa 02 ke seluruh jaringan, juga sebagai pembawa oksigen pernafasan di dalam sel urat daging (Underwood, 1981). Dalam duodenum dan yeyenum bagian atas, besi dalam bentuk ferro akan diserap. Penyerapan ini akan diatur berdasarkan teori "mucosal block" dari Granick. Kemudian dalam plasma darah, besi akan berikatan dengan B₁ globulin dan membentuk transferrin, yang akan segera dibawa ke seluruh jaringan. Kelebihan besi akan diikat oleh apoferritin dan membentuk ferritin yang ditimbun sebagai besi cadangan, terutama di hati. Bila kapasitas besi yang dapat disimpan sebagai ferritin telah jenuh, maka besi akan ditimbun sebagai hemosiderin. Zat besi dalam jumlah yang sedikit akan diekskresikan melalui pengelupas- an epitil, tinja, air kemih, cairan empedu, keringat. ...
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