Judul: Kendali Mutu Daun Jati Belanda (Guazuma ulmifolia) Menggunakan Pengolahan Citra dan Teknik Pengenalan Pola secara Kemometrik
Abstrak: Quality of medicinal plants affects the quality of the herbs. The quality of medicinal plant, as jati belanda leaf (Guazuma ulmifolia) can be determined using image processing. The objectives of the research were to make spectral imaging as a method for quality control of jati belanda leaves by evaluating the quality based on various harvesting and combined with chemometric pattern recognition techniques (PCA and PLSDA). Jati belanda leaf image with various qualities were reconstructed as reflection spectrum using Wiener estimation. Goodness of spectrum reconstruction was presented from root-mean-square-error value of 36.65 % and goodness-of-fit coefficient value of 0.9576. The preprocessing technique was applied to the reflection spectra to get the best classification and prediction model. PCA analysis on the jati belanda leaves with data preprocessing using two first principal component (PC) was 100% able of the total variants in the data (PC1 92%, PC2 6%, PC3 1%, PC4 1%). PLSDA analysis produced 3 models. The models were sufficiently successful in differentiating the quality of jati belanda leaves.
Keyword: quality control, PLSDA, PCA, jati belanda, image processing

Judul: Pendugaan Reflectance Berdasarkan Citra Digital Menggunakan Principal Component Analysis untuk Menduga Usia Daun Jati Belanda
Abstrak: Jati Belanda (Guazuma ulmifolia) is one of medicinal plants that contained various chemical components, one of them is flavonoid. Because of Jati belanda has many benefits in health sector, this plant was studied to control the quality of flavonoid in different ways, usually, chemical lab and tools are used for that experiment. Such process has high accuracy and fast, but it can damage the sample and required very high cost. Therefore, this paper discussed on development of a system that has function as quality control method to control the quality of medicinal plant leaf with spectral image using principal component analysis (PCA) and probabilistic neural network (PNN) is used to determining age of leaf based on value of estimated reflectance. The result of vale of estimated reflectance using PCA has RMSE value of 15.26 and GFC of 91.42%. In this research, identification system is builded by using polynomila order 2 and the first four components to predicting age of Jati Belanda leaf. Identification system has an accuracy of 86.67%.
Keyword: Bogor Agricultural University (IPB), Polynomial., Principal Component Analysis (PCA), Spectrum Reflectance, Guazuma Ulmifolia

Judul: Infeksi Virus Parainfluenza Pada Anjing
Abstrak: Virus parainfluenza anjing termasuk famili Paramyxoviridae, berbentuk pleomorf dengan ukuran bervariasi (bergaris tengah antara 100-500 nm), berpembungkus peka ether, berisi genom RNA dan secara serologis mempunyai kesamaan dengan virus SV-5 kera; dikenak sebagai salah satu kausa penting dari sindrom "kennel cough". Infeksinya dapat mengenai anjing semua umur yang belum pernah terinfeksi atau mendapatkan vaksinasi mengakibatkan gejala klinis ringan yang terbatas pada traktus respirasi atu infeksi yang secara klinis tidak memperlihatkan gejala nyata. Gejala klinis yang nampak setelah masa inkubasi (1-5 hari) terlewati berupa batuk yang tidak berat selama beberapa hari, berbagai tingkat tonsilitis dan pharyngitis dan kadang-kadang ditemukan kenaikan temperatur rektal antara 1-2 derajat C dari temperatur normal rat-rata. Anjing terinfeksi mengandung virus pada traktus respirasi bagian atas dan bawah serta limfonoduli sampai hari ke 9 setelah infeksi. Penyebaran virus antar anjing terjadi secara aerogen.
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