Judul: Remote Sensing Application and Spatial Database Design  For Sustainable Management of Coral Reefs in Banda  Island, South Maluku, Indonesia
Abstrak: Two LANDSAT-7 ETM satellite images of the study area were processed to apply the Bottom Feature Index and perform ISOclass unsupe~ised classification. The images were then mosaicked to create a classified image showing the entire archipelago of Banda Island. The result was a raster image with classified features deviating relatively less from actual measurements of area in Banda Island.
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Judul: Klasifikasi Ekosistem Terumbu Karang Berbasis Objek dan Piksel di Pulau Morotai
Abstrak: Most researches on the classification ofcoral reef benthic habitat mapping were conducted on pixel base analyses. This technique may lead to some extent of misclassification of coral reef ecosystem due to a high diversity and high spatial heterogenity. An alternative technique to reduce misclassification, an object-based image classification (OBIA) algorithm was proposed. This techniques first decomposed an image into relatively homogeneous objects or areas and then classified these objects (areas) instead of pixels. OBIA has been well developed and applied in terrestrial studies in past decades, but the method has not been used adequately on benthic habitat mapping. In addition to an image classification technique as one of the component in the analysis of remote sensing, the selection of a classification algorithm was also an important factor because it can largely affect the final result. Benthic habitat mapping studies of coral reefs are generally applied with traditional classification algorithms such as Maximum Likelihood (ML), which requires the spectral response of each class following the pattern of normal distribution (Gaussian distribution). In contrast to a contemporary algoritm, the machine learning algorithm has received more attention in the benthic habitat mapping for producing higher accuracy thanML classification algorithms. Currently, the machine learning algorithm has been widely used in the commercial remote sensing data processing both on pixel-based and object-based. The algorithm is also potential to be developed for coral reef ecosystem mapping. Application of an object-based classification technique with machine learning algorithm is still limited in Indonesia, especially for mapping of coral reefs, therefore, it requires an intensive study to develop this algorithm as an alternative for traditional algorithm. The general objective of this research was to identify the effectiveness of the application of satellite image classification techniques in generating detail mapping information of coral reef ecosystems. To achieve this objective, the following special objectives were developed: (1) to develop a systematic approach in the coral reef ecosystem classification to define the classification scheme, (2) to mapping coral reef ecosystems using object-based classification techniques with advanced classification algorithms (machine learning) on satellite image data, and (3) to assess status of coral reef ecosystems within the last few decades. Results of this study were expected to be used for consideration in the sustainable management of coral reefs ecosystem in the District of Morotai Island, especially in North Maluku, and can be used as a baseline to support the development of the field of mapping and remote sensing of coral reef ecosystems. This research was conducted in the coral reef ecosystem located in the western part of the Morotai island in North Maluku province. The study stepsconsisted of equipment preparation, data collection, data processing, and preparation of dissertation begins in September 2012. Field data collection was held in October 2012, while processing and data analyses were conducted from January v to September 2013. The method used in the study consisted of field data collection using the technique of line transects photo quadrat, pre-processing of Landsat 5TM, 7EMT + and 8OLI, the development of a classification scheme with ecological approach quantitative analysis based grouping in a hierarchical
Keyword: change detection, classification scheme, Morotai Island, object and pixel based classification, support vector machine

Judul: Peningkatan Ekspresi Transien Gen Eritropoietin (EPO) dengan Penambahan Asam Valproat dalam Sel CHO-K1 yang Diadaptasi
Abstrak: Eritropoietin (EPO) merupakan protein terapeutik yang banyak dimanfaatkan oleh penderita gagal ginjal untuk meningkatkan produksi sel darah merah. Protein EPO dapat diproduksi secara cepat dengan sistem ekspresi gen transien (TGE). Namun kendala dari TGE adalah produksi protein yang dihasilkan lebih rendah dibandingkan sistem ekspresi gen stabil (SGE). Penelitian sebelumnya menginformasikan bahwa inhibitor histon deasetilase (iHDACs), seperti asam valproat (VPA), dapat meningkatkan produksi protein rekombinan dalam sel mamalia dan mempunyai pengaruh yang berbeda-beda untuk tiap sel mamalia. Besarnya peningkatan dan pengaruh VPA terhadap produksi protein EPO pada sel CHO-K1 yang diadaptasi belum diketahui. Oleh karena itu untuk melihat besarnya peningkatan dan pengaruh VPA terhadap produksi protein EPO dalam sel CHO-K1 suspensi dilakukan beberapa parameter dan metode penelitian seperti optimasi konsentrasi lipofektamin sebagai agen transfeksi, optimasi konsentrasi VPA, karakterisasi protein EPO, pengukuran yield protein EPO, pengukuran densitas serta viabilitas sel CHO-K1. DNA plasmid pJ603-EPO berhasil ditransfeksikan ke dalam sel CHO-K1 dengan perbandingan konsentrasi DNA-lipofektamin yang paling optimum dan efisien untuk menghantarkan DNA plasmid pJ603-EPO masuk ke dalam sel CHO-K1 adalah 1:3. Protein EPO yang terekspresi secara ekstraseluler ke dalam media CHO-SFM berhasil dideteksi keberadaannya dengan anti-EPO pada ukuran sekitar 37 kDa. Struktur 5 N-glikosilasi pada glikoprotein EPO terkonfirmasi positif pada ukuran sekitar 22 kDa setelah dilakukan pemotongan dengan enzim N-glikosidase F. Konsentrasi VPA sebesar 4 mM merupakan konsentrasi yang paling optimum untuk meningkatkan ekspresi protein EPO. Penambahan VPA 4 mM pada produksi protein EPO yang diproduksi selama 12 hari menghasilkan yield protein EPO sebesar 14 mg/L, lebih tinggi 2 kali lipat dibandingkan produksi protein EPO tanpa penambahan VPA sebesar 7 mg/L. Data dalam penelitian ini menunjukkan bahwa VPA memiliki pengaruh yang kuat terhadap TGE. Ekspresi transien EPO dalam sel CHO-K1 suspensi yang diadaptasi meningkat hingga 2 kali lipat. Studi ini juga menunjukkan bahwa optimalisasi konsentrasi VPA sangat bermanfaat untuk mendapatkan peningkatan maksimum dalam ekspresi protein yang diinginkan.
Keyword: Asam valproat, CHO-K1, Eritropoietin, Inhibitor HDACs, TGE