Judul: Determination Of The Optimum Shooting Conditions In Estimating Paddy Leaf Color Level By Using a Handphone Cameras
Abstrak: Leaf color is an indicator that can be used to predict paddy fertilizer need. Handphone cameras can be used to measure the leaf color replacing the function of leaf color chart as the handphone technology has spread to farmer level. This research continues the previous research that still has low accuracy. The objective of the research is to determine the optimum shooting conditions in the estimation of paddy leaf color level using a handphone cameras. Rice leaf is slipped between user's finger on his/her palm, and the image is taken under body shadow. This image is then processed to get the RGB (red, green, blue) color components and then formulated with KNN to determine the color level. The KNN formulation was for every mobile phone type. It was found that the accuracy is affected by light intensity and the full fillment image frame. The best accuracy was found at 800-5000 lux light intensity and with a full frame image palms. The best accuracy was found to best shooting conditions with a image frame full of palm skin image at low light intensity, Samsung Ace was 87%, Sony Ericsson SK 17i was 93%, LG P698 was 91%, Samsung GT was 90%, Nexian was 93%.
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Judul: Estimation of chlorophyll leaves content in paddy plant (Oryza sativa) through leaves color level estimation with cellular phones
Abstrak: Paddy (Oryza Sativa) is one of the important cultivated plants in the civilization. Objectives of this research is to estimate chlorophyll content in paddy leaves (Oriza sativa) using leaves color chart and cellular phones. The results of estimation of leaf color level with the leaf color chart shows a high correlation with chlorophyll content (R2=0.9093). The higher levels of leaf color, then the higher the chlorophyll content (mg/g). The results of the estimation using a handphone is the estimation of leaf color levels and RGB components . Predictive accuracy of leaf color levels varies between 36%-47%. Accuracy of k-NN pattern recognition each cell phone varies between 34%-43% with an average of the highest accuracy in daytime. This accuracy is caused by the shooting conditions are not uniform and make RGB obtained inconsistent.
Keyword: RGB, SPAD, leaves color level, paddy, chlorophyll

Judul: Tuberkulosis pada satwa primata
Abstrak: Penyakit tuberkulosis pada satwa primata disebabkan oleh bakteri Mycobacterium yaitu Mycobacterium tuberculosis, Mycobacterium bovis, dan Mycobacterium avium, yang masing-masing menyebabkan tuberkulosis tipe human, bovin dan avian. Dari ketiga tipe tersebut, tuberkulosis tipe human adalah yang paling banyak ditemukan pada satwa primata. Ketiga tipe ini dapat dibedakan dengan melihat sifat-sifat bakteri pada pupukan dan virulensinya pada beberapa hewan percobaan. Kepekaan beberapa golongan satwa primata terhadap tuberkulosis berbeda satu dengan lainnya. Tuberkulosis tipe human dapat mengakibatkan kasus penyakit yang sangat fatal pada grup "Old World Monkey ", sedangkan "New World Monkey " tampak lebih resisten dan grup Prosimian jarang terkena tuberkulosis. Kasus tuberkulosis belum pernah ditemui pada koloni satwa primata yang hidup di hutan dan jauh dari pemukiman manusia. Tampaknya penularan yang terjadi pada satwa primata didapatkan dari kontak dengan manusia. Penularan tuberkulosis ini terutama adalah melalui inhalasi, kontak langsung, infeksi silang dari hewan-hewan jenis lain, juga dari peralatan yang terkontaminasi misalkan termometer rektal, tatoo, masker pembius dan tempat makanan. ..
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