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 grading system based on image processing and artificial neural network for green coffee sorting equipment with belt konveyor type
Abstrak: The objective of this research was to develop a grading system which consisted of a computer program of image processing and artificial neural network to identify quality of green coffee namely A, B, C, and RJ (reject). Two images of the green coffee from top and bottom captured by two cameras were analyzed to get six quality parameters which matched the green coffee quality criteria namely length, area, perimeter, defect area, index of red color, and index of green color. Those six quality parameters were used as training data inputs (75% - 768 kernel) of the developed artificial neural network (ANN). Eighteen variations of ANN were developed for ANN training purposes. The weight of the selected ANN architecture were used to identify the quality class of testing data (25%), and then integrated with image processing program so the program could identify green coffee quality class automatically. The total accuracy of ANN was 67% from top camera with A 59%, B 53%, C 70%, RJ 84%, and the total accuracy was 71% from bottom camera with A 75%, B 45%, C 73%, and RJ 92% based from 256 testing data. The total accuracy of ANN from combination of both cameras was 68%. New training was developed in order to increase prediction accuracy by modified ANN inputs. Prediction accuracy produced by the new ANN weight were A 78%, B 53%, C 70%, RJ 98%, and the total accuracy was 75%
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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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