Judul: Penentuan Subjek Otomatis Berbasis DDC pada Dokumen Perpustakaan miMenggunakan Algoritme Lin Similarity
Abstrak: Subject classification for library document with Dewey Decimal Classification (DDC) system is difficult to perform manually. The goal of this research is to make an application that automatically do perform subject classification for library document using similarity method. We use Natural Language ToolKit (NLTK) with Wordnet module to find similarity between keyword and DDC class. DDC is a hierarchy classification. We use Lin Similarity to find similarity between two words, with Brown corpus for Information Content (IC) of Wordnet. Wordnet can find similarity for only noun and verb, so we do not process other kinds of word. We use 30 documents combination of theses and dissertations in Bogor Agriculture University. We use 3 different methods to decide the relevant class of DDC which is similar to a document keyword. The first method is maximum-maximum method, the second one is maximum-average method, and the third method is maximum-minimum method. The first method results in 6 documents having the same main class, 2 documents having the same division class, and 0 document having the same section class. The second method results in 5 documents having the same main class, 1 document having the same division class, and 0 document having the same section class. The third method results in 3 documents having the same main class, 2 documents having the same division class, and 0 document having the same section class.
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Judul: Klasifikasi dokumen bahasa Indonesia menggunakan metode Dynamic Classifier Selection with Local Accuracies
Abstrak: Dynamic classifier selection with local accuracies (DCS-LA) uses k-Nearest Neighbor (kNN) to combine multiple classifiers. The purpose of this research is to compare classification performance using single classifiers (Rocchio, Bayes, and Bernoulli) with DCS-LA combining them. This research classified 249 agricultural documents (3 classes) and 750 news documents (5 classes). The single classifiers obtained different accuracies for the agricultural documents and the news documents. The accuracies for agricultural documents are 52%, 44%, and 61.34% for Rocchio, Bayes, and Bernoulli, respectively, while using news documents resulted in better accuracies, i.e., 81.6%, 86.4%, and 85.6% for Rocchio, Bayes, and Bernoulli, respectively. Similarly, the accuracy of DCS-LA is 56% and 86% for agricultural documents and news documents, respectively. This accuracy is higher than the average accuracy of single classifiers because of the local accuracy calculation in DCS-LA. The accuracy for the news documents is always higher than that of the agricultural documents, because the classes in agricultural documents are highly related. The relation can be seen from the percentage of common words shared among the classes. In the agriculture documents, in average of common words is 48% while it is 10% in the news documents.
Keyword: Classification, DCS-LA, Bayes, Rocchio, Bernoulli, Bogor Agricultural University, Institut Pertanian Bogor, IPB

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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