Judul: Klasifikasi Penutupan Lahan Hutan Mangrove di Kecamatan Buduran, Kabupaten Sidoarjo, Propinsi Jawa Timur, dengan Citra TerraSAR-X High Resolution
Abstrak: Indonesia actually has used remote sensing imagery in monitoring natural resources especially the optical image since apllied remote sensing technology. Indonesia’s position in the tropics cause the area always cover with clouds in most of the year. This condition affects the ability of an optical image to produce a clear image. Active remote sensing systems (radio detecting and ranging/Radar) has provided an alternative to overcome the limitations of the information than can be taken through an optical image data. TerraSAR-X, an earth observation satellite owned by Germany which was launched on June 15, 2007 at Boikonur Cosmodrome, Kazakhstan, is the latest radar technology for mapping the active wavelength X-band (wavelength 31 mm, frquency 9,6 GHz), which stated able to overcome the cloud cover. Since its launch, satellite TerraSAR-X has been in full operation starting in January 2008. The purpose of this research was to test the ability of high resolution image of TerraSAR-X for land cover classification and identification of constituent species of mangrove forests. Imagery used in this reseach consisted of the main image TerraSAR-X with HH and VV polarization that has made the extraction process to obtain the composition of RGB |HH|-|VV|-|HH-VV|. While the other supporting image are Quickbird image, distribution mangrove map of Sidoarjo regency and Sidoarjo regency administration map. The method used for classification of land cover types to make a class is supervised classification method and unsupervised classification method by reference to the results of the visual image interpretation. Then with the best classification method used for land cover classification process of mangrove forests. By appying the stratified classification method, it is expected to be able to reduce errors during the classification process. This is because the other objects than mangrove forests have been eliminated. The results showed the accuracy of the supervised classification by the method of Support Vector Machine (SVM) in the image of TerraSAR-X is the best method of classification with the overall accuracy of 77,93 % and kappa accuracy by 58,85 %. The value of mangrove forests on the classification accuracy using SVM and applying the two stage classification amounted to 90,74 % and kappa accuracy by 84,30 %. RGB image of the arrangement [HH - VV - (HH-VV)] of the dual polarization HH and VV can produce a 3 class contituent species of mangroves, that is Avicennia alba, Rhizophora mucronata and Xylocarpus molucensis class, Hibiscus tiliaceus class and shrubs and grasses class.
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Judul: Aplikasi dan Evaluasi Citra ALOS PALSAR Resolusi 50 m, Resolusi 12,5 m, dan Resolusi 6 m untuk Identifikasi Tutupan Lahan (studi kasus di Kabupaten Humbang Hasundutan, Kabupaten Tapanuli Utara, dan Kabupaten Samosir)
Abstrak: The application of remote sensing technology for rasionalization land resources data usage has more benefit than data collecting in conventional ways. Remote sensing techniques have been used in Indonesia for forest inventory and forest resources monitoring. Indonesia‟s geographical position where is in the tropics area that has vast cloud cover limits the use of optical satellite image data. To overcome the optical satellite image weakness, active remote sensing system (radar) is currently available. One of the satellites carrying radar sensor which was launched by the Japanese government is ALOS (Advanced Land Observing Satellite) with PALSAR (Phased Array type L-band Synthetic Aperture Radar) as its one of the sensor. This sensor is an active microwave sensor which has capability to penetrate thick cloud layer. The objective of this research is to analyze the ability of ALOS PALSAR satellite image of 50 m, 12.5 m, and 6 m resolutions on land cover classification at Humbang Hasundutan Regency, North Tapanuli Regency, and Samosir Regency. The observation has delivered 16 land cover classes, which are as follow: water body, harvested rice field, cultivating rice field, just-planted rice field, bushes, coffee plantation, dry land agriculture, town settlement, village settlement, bare land, nature forest, Eucalyptus plantation year 2010, Eucalyptus plantation year 2009, Eucalyptus plantation year 2006, Eucalyptus plantation year 2007, and Eucalyptus plantation year 2008. The result of digital interpretation of the ALOS PALSAR satellite image 50 m, 12.5 m and 6 m resolutions obtained 6 classes of land cover which are as follows: water body, rice field, dry land agriculture, settlement, bare land, and tree vegetation by different value of proportion correct. ALOS PALSAR of 50 m, 12.5 m and 6 m resolutions, each has proportion correct in consequence 62.1%, 50.5% and 68,9% Visual analysis, the result of ALOS PALSAR image with resolution 50 m obtained 8 classes of land cover,which are as follows: water bodu, dry land agriculuture, settlement, harvested rice field, young forest plantation, middle-old forest plantation, nature forest, dan bare land. Whereas, accuration and separability analysis of ALOS PALSAR image of 50 m resolution has regular accuracy value 59.15% and kappa accuracy 53.48%. The result of the interpretation raising-ability analysis of ALOS PALSAR image of 12.5 m and 6 m resolutions to the ALOS PALSAR image of 50 m resolution are able to provide additional land cover classes, clarify the delineation and make easier the identification of land cover at the satellite image.
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Judul: Dynamical System of Hepatitis B in Three Groups with Vaccination
Abstrak: The aim of this study is to modify the hepatitis B transmission model in three age groups involving vaccination from the model conducted by Zhoe and Zhang.The method used is to analyze the stability of the fixed point and its basic reproduction number (R_0). Performed stability analysis and numerical simulation to see population dynamics. Next, a sensitivity analysis of the parameters was carried out to see its effect on R_0. From the analysis obtained two fixed points, namely non-endemic and endemic fixed points. Non-endemic fixed points are locally asymptotically stable if R_0 <1 Meanwhile, the endemic fixed point is locally asymptotically stable if R_0 > 1. Hepatitis vaccination affects the number of susceptible population, because the more successful the vaccination, the smaller the number of susceptible populations so that the smaller the population will be infected.
Keyword: Dynamic, Hepatitis B, Vaccine, Mathematical model