Judul: Identifikasi Daun Shorea Menggunakan K-Nearest Neighbor dengan Ciri Statistical Textures
Abstrak: Various species of Shorea from Dipterocarpaceae family are dominating the lowland rain forests in Indonesia. Each species of Shorea has a unique function and can produce a high qualified timber in the construction industry. This research built an identification system of Shorea leaves using the statistical textures feature extraction with k-nearest neighbor as classifier. Statistical methods were utilized to analyze the spatial distribution of gray level values, by computing local features at each point in the image and deriving a set of statistical values from the distribution of the local features. The calculation of gray level values resulted in six parameters, namely mean, standard deviation, smoothness, third moment, uniformity, and entropy. A highest accuracy of 90% was obtained for the identification of 10 species of Shorea
Keyword: statistical textures, Shorea, k-nearest neighbor

Judul: Identifikasi shorea menggunakan k-nearest neighbour berdasarkan karakteristik morfologi daun
Abstrak: Dipterocarpaceae is a group of tropical plants that is used in a timber industry. One of Dipterocarpaceae clans is Shorea, that is the best timber-producing plant in the industrial world. Shorea is difficult to be identified because it has a lot of diversity. The inability to recognize Shorea in forest will enlarge the exploitation of Shorea that has a good timber quality, and silviculture work becomes less of the target because it is not known which Shorea species that will extinct. Shorea tree is usually identified by using the stems, leaves, fruits, and flowers. However, leave is used for the identification in this research because it tends to be available as a source of observation at anytime. The leaves in this reasearch are the collection from Bogor Botanical Gardens. Data are obtained by manual calculating to get the characteristics of the leaves. The obtained data will be processed using k-Nearest Neighbor to get the closeness of new data and training data. The leaves that are included in this research are Shorea multiflora, palembanica, balangeran, lepida and assamica, each one has 10 data. Each set of data has 10 attributes that support the leaf characteristics. From the whole data, Shorea are divided into five subsets including data training and data testing for each subset. This research has two experiments the first experiment without normalization produces 84% accuracy and the second experiment with a normalization produces 100% accuracy.
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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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