Judul: Peningkatan kinerja pelabelan otomatis citra menggunakan Bayesian Classifier pada temu kembali citra
Abstrak: This research proposes Bayesian Classifier to improve image annotation performance on image retrieval. Before being analysed by automatic annotation, descriptions of the image have to be known. Image description is the process of generating descriptions that represent the visual content of images in a certain manner, normally in the form of one or more features. Images are segmented into regions with grid segmentation. Each region are represented by a pre-specifed feature vector. The regions then clustered into a finite set of blobs. The correspondences between the blobs and the words are learned using Statistical Machine Translation and Bayesian Classifier. The experiment result shows that Statistical Machine Translation using Bayesian Classifier can improve precision as compared to Statistical Machine Translation. This method is promising to improve image query result on image retrieval.
Keyword: Content-based image retrieval, Automatic annotation, Statistical machine translation, Bayesian classifier, Latent semantic indexing, Bogor Agricultural University, Institut Pertanian Bogor, IPB

Judul: Improvement of Automatic Image Annotation Performance Using Bayesian Classifier on Image Retrieval
Abstrak: This research proposes Bayesian Classifier to improve image annotation performance on image retrieval. Before being analysed by automatic annotation, descriptions of the image have to be known. Image description is the process of generating descriptions that represent the visual content of images in a certain manner, normally in the form of one or more features. Images are segmented into regions with grid segmentation. Each region are represented by a pre-specifed feature vector. The regions then clustered into a finite set of blobs. The correspondences between the blobs and the words are learned using Statistical Machine Translation and Bayesian Classifier. The experiment result shows that Statistical Machine Translation using Bayesian Classifier can improve precision as compared to Statistical Machine Translation. This method is promising to improve image query result on image retrieval.
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Judul: Karakteristik Kimia Kayu Reaksi Ulin (Eusideroxylon zwageri T. et B.)
Abstrak: Reaction wood which formed in hardwood generally has a lower klason lignin content, higher acid soluble lignin content, and higher syringil unit than opposite wood. Ulin wood (E. zwageri) contains high klason lignin and low acid soluble lignin contents which closed to lignin characteristic of softwood. This experimental aimed to study the difference of chemical characteristic of reaction wood (klason lignin content, acid soluble lignin content, and lignin monomer composition) and polysaccharides content which formed in E. zwageri stem. Visually, the reaction wood part was formed in upper side of leaning stem. Klason lignin content in reaction wood part was lower (32.71%) than opposite wood part (33.74%). However, the lowest lignin content was found in the side wood part (28.15%). Lignin of E. zwageri was composed by syringyl and guaiacyl monomer with average of syringil to guaisyl ratio 0,2. Acid soluble lignin content in E. zwageri was very low (0.69%) that positively correlated with the proportion of syringil unit in lignin. Polysaccharide content of reaction wood part (63.66%) was higher than opposite wood part (62.88%), but the highest content polysaccharides presented in the side wood part (64.19%).
Keyword: Polisaccharide, syringil-guaiasyl ratio, lignin, E. zwageri, reaction wood