Judul: Pengkajian Algoritma Indeks Vegetasi Dan Metode Klasifikasi Mangrove Dari Data Satelit Landsat-5 TM Dan Landsat-7 ETM+ (Studi Kasus Di Kabupaten Berau, Kalimantan Timur)
Abstrak: Pemantauan mangrove dengan cara konvensional sangat sulit dilakukan karena kondisi lapangan menjadi hambatan yang besar bagi pelaksanaan survei. Penginderaan jauh merupakan alternatif dalam menjawab masalah-masalah yang berhubungan dalam manajemen mangrove. Tujuan studi ini adalah melakukan validasi data penginderaan jauh pada data Landsat-5 TM dan Landsat-7 ETM+, untuk menduga kerapatan kanopi mangrove, selain itu studi ini juga membandingkan dua metode klasifikasi, yaitu metode maximum likelihood dan neural network back propagation dalam memetakan mangrove. Hasil yang diperoleh menunjukkan bahwa transformasi indeks vegetasi yang paling baik untuk mangrove di Kabupaten Berau, Kalimantan Timur adalah green normalized difference vegetation index (GNDVI). Model matematis hasil principal component analysis (PCA) dalam menduga kerapatan kanopi mangrove adalah {2,5180 (-0,522x2 – 0,497x3 – 0,470x4 – 0,510x5)} + {1,3057 (-0,462x2 – 0,515x3 – 0,548x4 – 0,469x5)}. Klasifikasi neural network back propagation memiliki akurasi yang lebih baik dibandingkan klasifikasi maximum likelihood, dengan overall accuracy sebesar 85.61%.
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Judul: Mangrove Classification on ASTER VNIR using Vegetation Indices and Neural Networks Study Case : Berau Delta, East Kalimantan.
Abstrak: ASTER with its VNIR sensor have the capability for mapping vegetation. With the resolution of 15m x 15m, this image should be able to classify mangrove is more details than Landsat TM with resolution of 30m x 30m. Based on this, algorithms was applied to explore the capability of this image for classifying mangrove. These are Standard Back Propagation Neural Network and some vegetation indices (DVI, NDVI, SR, and the modified of these algorithm by using Natural Color Composite : NCC-DVI, NCC-NDVI, NCC-SR). While, as study area, Berau Delta, East Kalimantan is chosen because there are still may found many species of mangroves. Each algorithm show different results, but almost all of them capable to classify mangrove into zone level, except modification of vegetation index algorithms. Standard Back Propagation Neural Network is not quite good for classifying mangrove, because it can generate pixels into lower number of classes. While, DVI, NDVI, and SR can classify mangrove into 4 class. Its rather low than Maximum Likelihood Supervised classification and ISODATA Unsupervised classification which produced 5 class. But, when modified vegetation index applied, it a different results. They can detect Nypa fruticans class clearly than other species. Even, by using NCC-NDVI and NCC-SR class Nypa still can differentiate into detailer condition. The specific condition of the area of study where high frequency of rain, may cause the amount of water content in the vegetation become increase. Since gives influence in low value of NIR reflectance and high reflectance of RED channel, the modified algorithm of vegetation indices using NCC applied, and show result better than standard algorithm of vegetation indices.
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Judul: The Dynamic of HIV Virus Infection as a Result of Protease Inhibitor Therapy.
Abstrak: Acquired immunodeficiency syndrome (AIDS) is defined as symptoms of deterioration human immune system caused by human immunodeficiency virus (HIV). The virus damages the leucocytes; therefore, once a person infected by the HIV, his/her immune system will be paralyzed and eventually will not be able to survive from any disease. HIV is transmitted in many ways, such as having unsafe sex, using unsterilized syringe, blood transfusion, and many more. So far, there has not been discovered yet a way or a medicine that can totally cure this disease. However, reverse transcriptase inhibitor therapy, protease inhibitor, or combination of those two can decline the growth of virus inside the body of the infected person. Therefore, the immune system will be enhanced back to normal phase. In this paper, will analyze the effect of protease inhibitor therapy on the dynamics of virus inside the blood with different value of effectiveness. There are two mathematical models of protease inhibitor therapy to consider, i.e. perfect and imperfect protease inhibitor. The perfect protease inhibitor therapy hinders the virus to grow well and not to infect healthy leucocytes. On the other hand, the imperfect one cannot completely detained the virus growth.
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