Judul: Identifikasi Daun Shorea Menggunakan Probabilistic Neural Network dengan Normalisasi Fitur Morfologi Daun
Abstrak: Shorea is a timber plant from the genus of meranti. Shorea belongs to Dipterocarpaceae family which has 194 species growing in tropical area. The species of Shorea is difficult to be identified because of it is similarity to each other. This research utilized Probabilistic Neural Network (PNN) to classify Shorea species. The parameters used for classification were area, perimeter, diameter, smooth factor, form factor, perimeter ratio of diameter, perimeter ratio of physiological length and physiological width with 0.1 bias value. It was found that the accuracy of the proposed method was 100% (without normalization) and 91% (with normalization). It can be concluded that the morphological features of area, perimeter, diameter, and ratio of leaf length and width significantly affect the accuracy.
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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: Resistansi Escherichia coli yang Diisolasi dari Kucing di Klinik Hewan Kota Depok Terhadap Antibiotik
Abstrak: Kejadian resistansi antibiotik pada Escherichia coli pada hewan kesayangan sangat erat kaitannya dengan penggunaan antibiotik yang tidak tepat dalam waktu panjang dan tidak terkontrol. Penelitian ini bertujuan mengetahui gambaran resistansi E. coli yang diisolasi dari kucing rawat inap di klinik hewan Kota Depok terhadap antibiotik amoksisilin, gentamisin, sefotaksim, enrofloksasin, dan doksisiklin. Uji kepekaan antibiotik pada penelitian ini menggunakan metode Disk Diffusion Kirby-Bauer. Didapati sebanyak 12 isolat merupakan Escherichia coli. Hasil uji menunjukkan sampel resistan terhadap doksisiklin (sembilan isolat), amoksisilin (lima isolat), dan sefotaksim (lima isolat). Hasil intermediet ditunjukkan oleh amoksisilin dan sefotaksim, 16.7% resistan terhadap gentamisin, dan 8.3% resistan terhadap enrofloksasin. Escherichia coli pada penelitian ini masih cenderung sensitif terhadap gentamisin dan enrofloksasin., Antibiotic resistance in Escherichia coli in pets is closely linked to the long term and uncontrolled use of antibiotics. The study aims to determine the resistance of isolated E. coli cats in the City Depok veterinary clinic to the antibiotics amoxicillin, gentamicin, cefotaxime, enrofloxacin, and doxycycline. Antibiotic sensitivity test in this study using the Kirby-Bauer Disk Diffusion method. Twelve isolates were found to be Escherichia coli. The test results showed samples resistant to doxycycline (nine isolates), amoxicillin (five isolates), and cefotaxime (five isolates). Intermediate results were shown by amoxicillin and cefotaxime, with 16.7% resistance to gentamicin, and 8.3% to enrofloxacin. Escherichia coli in this study still tends to be sensitive to gentamicin and enrofloxacin.
Keyword: antibiotics, antibiotic resistance, escherichia coli