Judul: Geomorphological based small island and its ecosystems classification in Indonesia
Abstrak: Fishing in Indonesia remains as open access. As the largest archipelagic country in the world mostly comprising of small islands, Indonesia’s big shallow water area around small islands has an important role as fishing ground area ecosystem, thus need bordering to control access of fishery. Small islands and its marine ecosystems have high variety of biogeophysical characteristic which made it difficult to obtain information from. The use of satellite imagery to identify small island and marine ecosystem is still constrained by the availability of the proper image processing technique for the variety of characteristics. This research aims at selecting remote sensing data processing techniques in order to analyze the geomorphology of small islands and its marine ecosystems, classifying island type, designing identification of marine ecosystem and also designing small islands classification based on geomorphological characteristics for fishery planning. Study areas selected at small islands of Kota Batam, Kabupaten Sikka, and Kabupaten Sitaro. Several islands are selected to represent tectonic, volcanic, and reef type and to represent the main marine ecosystems such as mangrove, coral reef and sea grass. Landsat, SPOT and QuickBird images, along with Geological map, Topographic map, Navigation map and field survey are used to find out geomorphologic data of small islands. Steps on image processing composed of multispectral fusion, enhancement and multispatial fusion techniques. Small islands geomorphological analysis method consists of morphology, morphogenesis, morphochronology, and morpho-arrangement aspects which are conducted by landforms identification by landscape approach. Correlation between small island and shore fishery is analyzed by the number of fish species on seven locations with 3 and 10 meters depth using diversity, uniformity, and dominancy indexes.
Keyword: marine ecosystem, island type, remote sensing, classification and identification

Judul: Geomorphological Zone and  Benthic Habitat Mapping Using SPOT-7 Imagery in Kelapa and Harapan Island
Abstrak: Perairan dangkal mempunyai ekosistem yang berkaitan yakni lamun, mangrove, dan karang. Geomorfologi merupakan ilmu yang membahas bentuk muka bumi. Bentuk muka bumi yang terbentuk pada laut mempunyai kedalaman tertentu. Adanya satelit SPOT-7 yang memproduksi citra resolusi tinggi menghasilkan metode Object Based Image Analysis (OBIA). Penggunaan algoritma Support Vector Machine (SVM) pada metode OBIA menghasilkan akurasi yang tinggi. Penelitian ini dilakukan pada perairan Pulau Kelapa dan Harapan, Kepulauan Seribu, DKI Jakarta. Penggunaan metode OBIA dan klasifikasi algoritma SVM dengan 3 level segmentasi. Level 1 menghasilkan 3 kelas yaitu, perairan dalam, perairan dangkal, dan darat. Hasil klasifikasi level 2 menghasilkan 4 kelas zona geomorfologi dengan berbagai kedalaman yaitu, crest, slope, flat, dan lagoon. Zona flat mendominasi lokasi penelitian. Keempat zona tersebut dapat dipetakan kedalamannya dengan baik. Klasifikasi level 3 menghasilkan 6 kelas yaitu DCA, karang, lamun, rubble, makroalga, dan pasir. Kelas lamun mendominasi area penelitian. Akurasi secara keseluruhan yang didapatkan mencapai 76.47%., Shallow water has some ecosystem that links each other: seagrass, mangrove, and coral. Geomorphology is a science about the shape of the earth's surface. The surface of the planet has a different depth. The appearance of the SPOT-7 imagery satellite that produced high-resolution images developed the Object-Based Image Analysis (OBIA) method. Using the Support Vector Machine (SVM) algorithm in the OBIA method has high accuracy results. This research took place in Kelapa and Harapan Island, Kepulauan Seribu, Jakarta Province. OBIA method and classification using SVM algorithm for 3-level segmentation. Level 1 obtained three classes: deep water, shallow water, and land. Classification level 2 received four categories for geomorphology zone, with the difference in depth: crest, slope, flat, and lagoon. The flat area dominated the research location. The bathymetry of all the four-zone got mapped well. Classification level 3 generated six classes: DCA, coral, seagrass, rubble, macroalgae, and sand. Seagrass class dominated the research area. The classification results produced an overall accuracy value of 76.47%.
Keyword: Geomorphology Zone, Benthic Habitat, SVM, SPOT-7, OBIA

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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