Judul: Klasifikasi Freycinetia Berbasis Citra Anatomi Stomata Menggunakan K-Nearest Neighbor dan Jaringan Syaraf Tiruan
Abstrak: The classification of Freycinetia is conducted to portray the potential result and function of nutfah plasma spreader. This research is purposed to classify a variety of Freycinetia based on stomata anatomic image by K-Nearest Neighbor (K-NN) and Artificial Neural Network (ANN). The Variety of Freycinetia classification can be described by using two different ways that are morphology and anatomic characteristic. Stomata anatomic image is used to support morphology characteristic in the identification process, especially in uncompleted morphology image specimen and sample. There are two feature extraction techniques in this research. First, is to pick up the color and gray scale element in the image. The scale element has a red, green and blue color (RGB). The grayscale has an entropy, contrast, energy, homogeneity, gray scale and deviation standard. Second, is a wavelet decomposition technique which has a function for decreasing a size of the image without loosing its important element. The taken element becomes a coefficient image of w-entropy for each wavelet level. Ninety six data is used in this research, it contains of four kinds of Freycinetia. They are Freycinetia angustifolia, Freycinetia imbricata, Freycinetia javanica, and Freycinetia sumatrana. The result shows an accuracy level for K-NN according to RGB and gray scale is 86.46% and according to wavelet decomposition is 96.88%. Whereas, the accuracy level of ANN based on RGB color and gray scale element is 94.79% and according to wavelet decomposition is 9 9%. The classification result of plant variety, especially Freycinetia based on stomata image with high accuracy, will be an alternative tool to identify taxonomy type.
Keyword: 

Judul: Identifikasi Freycinetia Berbasis Citra Anatomi Epidermis Daun Menggunakan k- Nearest Neighbor
Abstrak: Freycinetia identification was conducted to determine the potential values, benefits, and distribution patterns as a biodiversity in Indonesia. The purpose of this research was to compare the low frequency and high frequency in Freycinetia identification based on leaf epidermis anatomy image by k-Nearest Neighbor (k-NN). Identification of Freycinetia can be described by using morphology and anatomy characteristics. Leaf epidermis anatomy image was used in the identification process to support the morphology characteristics, especially in speciment and sample with incomplete morphology. This research analyzed ninety six data which contains four kinds of Freycinetia, namely Freycinetia angustifolia, Freycinetia imbricata, Freycinetia javanica, and Freycinetia Sumatrana. The data were transformed by Fourier transformation and filtered in frequency domain to take the low frequency of image and the high frequency of image. It was found that the accuracy of k-NN with low frequency was 90.625% and that of the high frequency was 81.25%. These accuracy values indicated that in the identification of Freycinetia based on leaf epidermis anatomy image by k-Nearest Neighbor (k-NN), the use of low frequency is better than high frequency
Keyword: 

Judul: Proses Memperoleh Daging Sapi yang Baik dan Sehat untuk Konsumen
Abstrak: Tingkat konsumsi protein hewani asal ternak menjelang tahun 1968 hanya sekitar 1.20 gram per kapita per hari . Seirama dengan perubahan besar dalam penanganan masalah ekonomi yang dilaksanakan oleh Pemerintah, dapat diperkirakan bahwa permintaan efektif akan daging sapi pada masa-masa yang akan datang akan terus meningkat.Demikian pula perkembangan tingkat kesadaran gizi akan mengakibatkan meningkatnya kebutuhan akan daging sapi, baik secara kualitatif maupun kuantitatif .
Keyword: