Judul: Identifikasi Pola Hutan Rakyat dan Penutupan Lahan Lain Menggunakan Citra Landsat 8 OLI (Studi kasus di Asosiasi Petani Hutan Rakyat Wonosobo)
Abstrak: Landsat 8 is new satelit has a sensor Operational Land imager (OLI) with a spatial resolution 30m x 30m and consist of eight spectral bands. Data and informations about comunity forest land cover is rarely done. The aims of this research are to identify comunity forest type and other land cover by use Landsat 8. The using method supervised classification in research are maximum likelihood and Support Vector Machine (SVM). Based on separability analysis using eight spectral bands, the type of comunity forest in APHR Wonosobo turned out not to be identified with either and acquired six land cover classes are residential, water body, shrub/dry land farming, rice field, open land, and mixed farm. The best method to classify land cover in APHR Wonosobo is maximum likelihood method with value of Kappa accuracy of 76.59% and has a high conformity by the visual image interpretation.
Keyword: Bogor Agricultural University (IPB), maximum likelihood, supervised classification, Landsat 8, Land cover

Judul: Identifikasi Karakteristik dan Pemetaan Klasifikasi Tutupan Lahan Menggunakan Citra Landsat 8 (OLI) di Kabupaten Bogor
Abstrak: Landsat 8 is the new generation satellite from Landsat Program that is LDCM (Landsat Data Continuity Missions). Landsat 8 has a sensor OLI (Operational Land Imager) with a spatial resolution of 30 x 30 m and consist of eight spectral bands. The result of calculation for the best combination for land cover using OIF (Optimum Index Factor) is band 754 combination. On Landsat 8, band 7 is the spectrum of SWIR-2, band 5 is the spectrum of NIR, and band 4 is the spectrum of red. The results of land cover classification in Bogor Regency using maximum likelihood method is able to distunguish 15 classes of land cover in Bogor Regency, i.e pinus forest, recent planted paddy, rubber plantations, settlement, cloud, cloud shadows, water body, barren land, airports, fruit farms, oil palm, dense forest cover, shrubs/bush, ready harvest paddy, and mixed farms. Accuracy result from classification show a high accuracy value that 92.18% for overall accuracy and 90.61% for kappa accuracy. This result shows that the classification result of Landsat 8 mapping is usable.
Keyword: land cover, Landsat 8 (OLI), combination band

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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