Judul: Pengenalan citra wajah menggunakan algoritme VFI5 dengan praproses principal components analysis
Abstrak: Pattern recognition is a scientific discipline for the classification of objects into a number of categories or classes. Today, one of the intensive researches in the field of pattern recognition is face recognition. In this research, we tried to perform face recognition by using Voting Feature Interval 5 (VFI5) classification algorithm. VFI5 algorithm is an algorithm that represents a description of a concept by a set of feature intervals and performs classification based on the voting feature. Features used in this research were generated from gray level face images. The face image dimension is 112×92 pixels which means there will be 10304 features which caused difficulties to achieve better accuracy with less storage and computational complexity. For that, Principal Components Analysis is used to reduce the dimensions. This is done by projecting an image on eigenface. Eigenface is obtained by projecting training data on eigen vector. Experiments were performed by using cross validation. Ten fold cross validation was used as cross validation technique with 10 repetition of single observation from the original sample as the validation data and the remaining as training data. The result of 10 observations subset are respectively 80%, 100%, 90%, 100%, 90%, 100%, 100%, 90%, 100% and 90%. Resulting in an average accuracy of 94%. We conclude the VFI5 algorithm good at recognizing face images.
Keyword: Image processing, Face recognition, Principal components analysis, VFI5 algorithm, Bogor Agricultural University, Institut Pertanian Bogor, IPB

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: Salinity influence to mercury toxicity and the effect to milkfish (Chanos chanos Forsskal) physiologic conditions
Abstrak: Mercury is a very dangerous heavy metal that can damage nerve and enzyme system in fish body. This research aimed to knows mercury toxicity to milkfish with different salinity. It consisted of two steps; they were preliminary research (range value test and acute toxicity test) and main research (the salinity influence of mercury toxicity and milkfish’s physiologic condition). Range value test was done in fresh water consisting of five treatments (0, 0.006, 0.06, 0.6 and 6 mg Hg/l). Acute toxicity test also consisted of five treatments (0, 0.110, 0.195, 0.347 and 0.618 mg Hg/l). Moreover, main research consisted of one control and three treatments with three replications at the same concentrate of mercury 0.012 mg Hg/l. Those treatments were salinity 0 ppt, 10 ppt and 20 ppt. The result demonstrated that LC50 96 hour in fresh water was 0.147 mg Hg/l. The main research showed that mercury can increased osmotic gradient, decreased oxygen consumption rate, increased blood glucose rate, decreased hematologic conditions, growth rate, feeding efficiency, and survival rate. Mercury is collected in body gland, for example in gill and liver. Treatment C (10 ppt) showed better physiologic conditions than other treatments. The effect of mercury toxicity would get minimal while maintained at optimal salinity.
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