Judul: Pengenalan Genus Diatom Menggunakan Principal Component Analysis dan Jaringan Syaraf Tiruan Backpropagation sebagai Classifier
Abstrak: Diatoms are unicellular algae which have a size between 2 μm and 4 mm. Their importance resides in the fact that they can be used in several research and scientific fields. For instance, they can be used to measure sediment pH, medicinal, as water quality indicators, etc. The recognition and identification of diatoms is a tedious work. This classification process is complicated even for the experts, because there are hundreds of different taxa with many variations in shapes and biological characteristics. This research apply Principal Component Analysis (PCA) for data reduction and Artificial Neural Network (ANN) to identify some kind of diatoms. The proportion of PCA are used in this research is 80% and 90%. This proportion is considered to replace the original data without much loss of information. Backpropagation ANN that used is a single hidden layer. The data used in this study is a JPG image of diatom sampling using electric microscope taken from Biomikro Laboratory, The productivity and Water Environment, Department of Water Resources Management, Faculty of Fisheries and Marine Science, Bogor Agricultural University. All images are divide using two scenarios percentage. The first scenario divide 60% for training data and 40% for testing data, while the second percentage is 80% for training data and 20% of testing data. As result, ANN can be used to identify diatoms. The results showed that the best generalization rate of 90% was obtained in an experiment using 90% PCA proportion with 80% of training data and 20% of testing data.
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Judul: Pengembangan wahana pencitraan bawah air guna identifikasi dan kuantifikasi terumbu karang dengan metode jaringan syaraf tiruan
Abstrak: Initially finger printing methods was used by police for criminal case investigation; then expanded to other practical application. Artificial Neural Network is one of the technique to process data to identify and recognize a particular pattern similar to the way human brain functions. In this thesis, I investigate and identify various coral features using artificial neural network (ANN) back-propagation method. The underwater vehicle was constructed to collect coral imagery, using; stainless steel body with two floats on the left and right and equipped with camera, GPS-map sounder, and light sources. The 3000 images were collected and pre-processed, to extract descriptor or key parameters of the features, during field measurements. The ANN back-propagation applied to identify the life form as sub-massive coral has an accuracy of 92.86%. Therefore, the application of this technique for features identification of the coral life form is recommended..
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Judul: Kawin Berulang Pada sapi, Kausa Kuman Aspesifik Dan Pengobatannya
Abstrak: Kawin berulang pada sapi betina adalah merupakan bantuk atau geja1a inferti1itas, dimana sapi-sapi yang menderita kawin beru1ang tersebut mempunyai siklus berahi yang normal atau hampir normal dan sudah dikawinkan dua ka1i atau 1ebih dengan pejantan atau semen pejantan fertil, tapi tetap belum bisa bunting. Pemeriksaan klinis terhadap sapi tersebut tidak memberikan gambaran tertentu yang dapat menerangkan kegaga1an konsepsi yang dialami (Roberts, 1971).
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