Judul: Relevance Feedback pada Temu Kembali Citra Menggunakan Bayesian Network
Abstrak: Query results not always match with user's desire. The key issue in relevance feedback is how to utilize the feedback information to improve the retrieval performance. This research proposed a method of relevance feedback using the Bayesian network model. Research data consists of 550 images which are grouped into 11 classes. The information concern in this model are histogram-l 62 for color infonnation, gradient for shape information and co-occurrence matrix for texture infOlmation. This research used Rocchio as relevance feedback algorithm. Re-weighting in feature vector used inter-weight and intra-weight updating theory. The weights that have been updated then it was used as posterior probability, and also used as a rank ofrelevant image. Evaluation of retrieval result is computed using average value of precision, the results showed that average value of precision for all classes is increasing about 4.7959% on Bayesian network model with relevance feedback compared with Bayesian network model without relevance feedback. Through the results, this research can improve the retrieval perfonnance in CBIR.
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Judul: Optimisasi Query Citra dengan Relevance Feedback dan Support Vector Machine
Abstrak: Temu kembali citra dilakukan berdasarkan isi citra (CBIR). masing-masing citra memiliki warna, bentuk dan tekstur yang beragam sehingga perlu digunakan teknik klasifikasi agar proses pencarian dapat bekerja optimal. Relevance Feedback (RF) digunakan untuk lebih memaksimalkan hasil temu kembali citra. Penelitian ini menitikberatkan pada temu kembali citra berdasarkan ciri warna. Citra query disegmentasi menggunakan Expectation Maximization kemudian diekstraksi dengan Fuzzy Color Histogram (FCH). Kelas dari citra query diperoleh dari model klasifikasi yang dibentuk menggunakan Support Vector Machine (SVM). RF akan melakukan update pada FCH query sesuai masukan dari pengguna. Penelitian ini mengukur peningkatan yang terjadi pada temu kembali citra dengan SVM dan RF dibandingkan dengan SVM tanpa RF. Evaluasi hasil temu kembali menggunakan rataan precision untuk tiap tingkatan recall. Berdasarkan penelitian ini, hasil temu kembali citra menggunakan SVM tanpa RF memiliki rataan precision 0.74, sedangkan hasil temu kembali ctra menggunakan SVM dan RF memiliki rataan precision 0.82.
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Judul: Analisis Sekuens Gen Penyandi Enzim Xilanase Ekstraseluler pada Streptomyces costaricanus 45I-3
Abstrak: Streptomyces costaricanus 45I-3 isolated from peat soil is a bacterial strain in the group of actinomycetes. This bacterium is known to produce extracellular xylanase. The objectives of this study were to analyze sequence of gene involved in the synthesis of extracellular xylanase. Complete gene encoding xylanase was isolated from the bacterial genome by Inverse Polymerase Chain Reaction (i-PCR). The resulted gene sequence in a total alignment of 1664 bp amplicons, which consisted of two open reading frame (ORF) with opposite direction. ORF1 consisted of 1029 bp and ORF2 (Partial sequence) consisted of 309 bp. BLASTX analysis showed ORF1 homology with xylanase of bacterium enrichment culture clone Xyl8B8 (GenBank accession No. AFH35005.1) that had 95% identity and 99% similarity. ORF2 homolog with glyoxalase bacterium enrichment culture clone Xyl8B8 (GenBank accession No. AFH35007.1) that had 95% identity and 98% similarity. Upstream of the ORF1 sequence was found Ribosome Binding Site (RBS) 7 bp from the start codon and putative promotor sequence at 100 bp (-35) and 77 bp (-10) from the start codon. Analysis of protein sequence deduced from ORF1 showed that there were 2 domains, i.e Glyco_hydrolase 11 (GH11) and Carbohydrate Binding Type 2 (CBM2). Active sites found on the 130 amino acid on GH11 domain. Visualization of 3 dimension structure showed that 1664 bp fragment had 19 area.
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