Judul: Penyusunan tabel isi pohon untuk jenis Shorea spp dan Dipterocarpus spp di kawasan hutan Propinsi D.T. I Riau
Abstrak: Tujuan penelitian adalah untuk mendapatkan tabel isi pohon yang cermat untuk jenis Shorea PP dan Dipterocar­spp. di kawasan hutan Propinsi Daerah Tingkat I Riau berdasarkan persamaan-persamaan regresi. Pengamatan dan pengukuran pohon contoh dilakukan di tiga blok tebangan yang bertipe hutan hujan tropik bawah, hutan sambut dan hutan rawa. Model acuan untuk pohon normal adalah model logaritmik Schumacher dan Hall. Koreksi model dicobakan pada ukuran diameter pohon-pohon tak normal. Tabel isi pohon untuk jenis Shorea spp. dan Dipterocar spp. pada hutan hujan tropik bawah Propinsi Daerah Tingkat I Riau dapat diturunkan dari sebuah persamaan regresi. Sedang untuk jenis Shorea spp. pada tipe hutan hujan tropik bawah, hutan gambut dan hutan rawa masing­ masing harus diturunkan dari sebuah regresi yang berbeda satu sama lain. Koreksi model yang dilakukan pada ukuran diameter pohon-pohon tak normal sangat berguna sekali.
Keyword: Dipterocarpus

Judul: Identifikasi jenis shorea menggunakan jaringan syaraf tiruan propagasi balik berdasarkan karakteristik morfologi daun
Abstrak: Dipterocarpaceae is a major timber tree of tropical rain forest. Shorea is a genus of the Dipterocarpaceae family which consists of around 194 species. Species diversity may lead to difficulty in distinguishing species of Shorea of one another. It takes knowledge from an expert in the field of Shorea to be able to identify the types of Shorea. Errors in identifying the type of Shorea wood can lead to inappropriate selection for the final usability. Identifying the type of Shorea carried out on five species of Shorea owned Bogor Botanical Gardens on the basis of morphological characteristics of leaves. The identification was carried out using Backpropagation Neural Network. To obtain the values of each leaf morphological characteristics of Shorea, each sample measurement data collected manually. The values are then processed using Backpropagation Neural Network to get the pattern from the training and the accuracy of the test phase. This research used a total of 50 data from five species of Shorea. The data are divided into five subsets. The fifth subset is used in the training and testing phases and conducted five times. The use of methods Backpropagation neural networks in identifying species Shorea produces an average accuracy of 90%.
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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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