Judul: Identifikasi Jenis Shorea Menggunakan Jaringan Syaraf Tiruan Propagasi Balik Resilient Berdasarkan Karakteristik Morfologi Daun
Abstrak: Shorea (Meranti) is one of the best kind of wood from tropical forests in Indonesia, and one of the best timber of the family Dipterocarpaceae. Shorea has the highest species diversity among its family, which consists about 194 species. This makes it difficult to identify the species of Shorea. Experts in the field of automatic Shorea identification is still rare. Hence, identification using the morphological characteristic of Shorea leaves is more preferred. This research is focused to identify Shorea species using morphological characteristics of leaves. The data used are manual measurement from a sample of the leaves which are taken from each type of Shorea ovalis, Shorea leprosula, Shorea platyclados, Shorea seminis, and Shorea beccariana. Sample of the leaves is taken from the Shorea collection at the Bogor Botanical Gardens. Classification model is built by using resilient backpropagation neural network. After the data has been collected, the feature values of these five species of Shorea is used in the experiment for training and testing the resilient backpropagation neural network. In the training process, we use a variation of the resilient backpropagation neural network parameters in a 5-fold cross-validation experiment. Each experiment unit is divided into two types: with regression and without regression. Overall, the accuracies of the experiment was 98%. Both types produce the same accuracy with different resilient backpropagation neural network optimal parameters, and the same incorrect identification, which is an instance of Shorea leprosula being identified as an instance of Shorea ovalis.
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Judul: Klasifikasi Jenis Shorea Berdasarkan Morfologi Daun Menggunakan Jaringan Syaraf Tiruan Propagasi Balik Levenberg-Marquardt
Abstrak: Shorea belongs to the Dipterocarpaceae family and is one of tropical rain forest plants which is being used in timber production. Due to the existence of its various species, Shorea’s identification remains a challenge. The aim of this research was classifying Shorea’s species using Levenberg-Marquardt Backpropagation Neural Network based on 23 morphological characteristics of its leaves. This research utilized the data from 10 species of Shorea that lived in Bogor Botanical Garden, with 10 samples each. Those species were Shorea johorensis foxwf, Shorea pinanga sp, Shorea macroptera dyer, Shorea leprosula miq, Shorea lepida blume, Shorea materialis ridley, Shorea platyclados, Shorea javanica koord & val, Shorea palembanica, dan Shorea seminis. It was found that a 100% identification accuracy can be obtained with Hidden Neuron 8 and 10.
Keyword: Backpropagation, Levenberg-Marquardt

Judul: The Control And Eradication Of Brucellosis In Cattle From The Standpoint Of Human Health
Abstrak: Brucella abortus occurs both in man and cattle. The organism may thrive wherever cattle are raised by man for breeding purposes. As such, spread to humans can easily be lessened if the disease is properly controlled and/or eradicated in cattle. Control of Brucella abortus in cattle can be under taken by continued vaccination, proper attention to hygiene and the particular care taken in the introduction of only brucellosis-free animals into cattle farms. Vac- cination using the strain 19 or strain 45/20 Brucella abortus vaccine is commonly used, though the former is more popular. Each of these vaccine strains has its own advantages and disadvantages. Eradication of Brucella abortus by the test and slaughter policy can also be carried out after proper vaccination programmes have been initiated and a stage reached where only a very small percentage of positive reactors is found,
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