Judul: The Development of Soybean Grading Algorithm Using Image Processing and Artificial Neural Network
Abstrak: Grading method influences the homogeneity of each grade of such product and a good grading method provides producer and consumer with standard for the price of the product. The objective of this research was to develop a computer program of image processing and artificial neural network to identify the quality of fresh soybean into four classes namely SQ (standart quality), SG (second grade), TG (third grade), and RJ (reject) using image processing and artificial neural network. The total samples were 2500 fresh soybean produced by PT. Mitra Tani Dua Tujuh Jember. Soybean image was analyzed to get six quality parameters whose match with soybean quality criteria namely pod length, pod area, perimeter, defect area, index of red color, and index of green color. Those six quality parameters will be used as inputs of the artificial neural network (ANN). Six variations of ANN were developed for ANN training purposes (2000 data). The weights of the selected ANN architecture was used to identify the quality class of testing data (500 data), then integrated with image processing program so the program could identify soybean quality class automatically. The quality parameter used in this research has relevancy with soybean quality criteria. The selected architecture of the ANN was the one with 20 nodes hidden layer in which normalization input data representation with zero mean and standard deviation equals one. The accuracy of image processing program observed 81, 4 percent based on the 500 testing data.
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Judul: Development of machine for evaluating quality of rice by using real time image processing
Abstrak: Quality assessment of rice prior to marketing is very important. Up to now, the rice quality inspection is conducted visually by trained examiners who have expertise and experience, but the method used has disadvantages such as: (1) the subjectivity factor that causes rice quality testing results to be biased between the observer, (2) the physical exhaustion of observer causes the observation result is inconsistent, and (3) the time required relatively much longer. The purpose of this study was to develop a method of determining the physical quality of rice by image processing techniques in real-time. The method used was the technology of image processing and artificial neural networks. Architecture of ANN to predict the physical quality of rice was built with 13 input layers, 20 hidden layers and 8 output layers, while the ANN to predict the degree of rice milling was built with 9 input layers, 20 hidden layers and 5 output layers. The results showed that the machine for testing rice physical quality in real time had worked functionally as expected, both hardware and software. The training process of the 5 rice varieties showed good results, especially in the estimation of head rice which was above the average 90 %, whereas the accuracy of validation decreased due to predictive accuracy of foreign matter dropped drastically due to the irregular shape and varied colors, making it difficult for the system to recognize it. The test results show rice milling training and validation results are not consistent, so it can not be resumed in the application process.
Keyword: Rice, quality, real-time image processing, artificial neural network

Judul: Psittacosis Sebagai Zoonosis Penting Yang Berasal Dari Burung
Abstrak: Psittacosis atau ornithosis adalah penyakit menular dari burung kepada manusia. Agens penyebab psittacosis termasuk ke dalam virus psittacosis-lymphogranuloma venereum group yang disebut Chlamydia psittaci. C. psittaci hanya dapat berkembang biak di dalam jaringan hidup tetapi peka terhadap antibiotik. Penyebaran penyakit ini sangat luas, terdapat hampir di seluruh dunia. Di Indonesia penyakit ini belum pernah di diagnosa, tetapi mengingat terdapat demikian banyaknya jenis burung maka diperkirakan psittacosis ini sudah ada. Kasus pada manusia pertamakali ditemukan oleh Ritter pada tahun 1879, di Eropa. Waktu itu dikenal sebagai pneumotyphus. Chlamydia psittaci tidak hanya sebagai penyebab infeksi pada burung, juga bisa menyebabkan infeksi pada mamalia diantaranya sapi, kerbau, kambing, domba, babi dan kucing. Pada kucing dikenal sebagai feline pneumonitis. Pada domba atau kambing mengakibatkan enzootic abortion. Pada burung, kalkun merupakan unggas paling rentan diikuti oleh burung psittacine dan burung lain di luar famili psittacidae. Virulensinyapun berbeda-beda. Yang berasal dari kalkun bervirulensi tinggi, sedangkan yang berasal dari burung merpati bisa bervirulensi tinggi bisa juga bervirulensi rendah. Penularan terjadi melalui kontak langsung maupun ti- dak langsung. Penularan melalui telur tidak terjadi. Umumnya penyakit ini memperlihatkan gejala klinis berupa deman, lesu, lemah, anorexia, kurus, diarrhea ber- warna kekuningan, discharge dari mata dan hidung, conjunc- tivitis. Gejala khas pada kalkun adalah istirahat dengan sternum sebagai dasarnya, karena adanya tekanan dari bagian perut yang sakit. Sedangkan pada manusia memperlihatkan adanya demam, kadang-kadang merasa dingin, lesu, sakit kepala yang hebat, sakit pada bagian belakang badan dan photophobia…dst
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