Judul: Determining Best Location of New Bakosurtanal Outlet Using GIS with Multicriteria Density Analysis.
Abstrak: As a government institution that holds survey and mapping activities in Indonesia Bakosurtanal has costumers spread out around this country. For about 75% of that costumers are from Jabodetabek area. Until today, product selling transaction is held by center outlet of Bakosurtanal, Cibinong, West Java and several outlets in Jabodetabek. The number of outlets in this area are not balance with the number of costumers. Thats why, Bakosurtanal plans to build several new outlets to increase services for its costumers. To determine the best location of new outlet, several factors need to be considered, such as customers and facilities spread out data. Geographical Information System (GIS) and several analysis process can be utilized to answer this big question. Determining Best Location of New Bakosurtanal Outlet Using GIS with Multicriteria Density Analysis is developed using arcGIS 9.2 software from ESRI. The primary goal of this experiment is to determine best location by considering density of all parameters. The parameters are costumers and facilities spread out data. The process is started from data clearing. This step is aimed to get unique and complete addressed costumers data. The following process is digitizing. In this step every costumers are mapped to the digital map by defining their spatial coordinate based on their real and complete addresses. The output of this step are point shapefiles. Survey is done to know the real position of costumer’s uncertain address. Beside it, the survey is aimed to get costumer’s opinion about best location of new outlets. When the point shapefile has been created, point density process can be started. All costumers and facilities data of every area are proceed to get their each density, and then they are classified to be 5 classes for every layer. The output of point density are raster image. The next step is overlaying. Overlay process is done between raster image of costumer and facilities. Unfortunately, all parameters do not have same influence to decide the best location. Thats why every raster image must be given weight. The weight of every raster image can be gotten by doing buffering and clipping. Both process are done to get information about how big facilities influences the costumers density. If there is positive correlation between facility and costumers, that facility will be given a big weight. In the contrary, it will be given small weight. How we give the weight of every facility is also depend on costumers opinion, based on the survey. When all facilities have been weighted, the overlay can be started. The output of overlay are shapefiles that can show best location of new outlet of every area. Keyword: GIS, density analysis, Bakosurtanal
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Judul: The Integration of Spatial Data WMS and KML Format with Google Maps in Bakosurtanal WebGIS.
Abstrak: The development of Geographical Information System (GIS) technology nowadays has increased the needs of data services. The spatial data can be distributed to each institution through a standard provision of access to spatial data such as Web Map Service (WMS) and Keyhole Markup Language (KML). Google Maps, a service provider of maps and satellite images, provides an easy way for WebGIS developers to create their own composition maps. Google Maps can be integrated with spatial data, the WMS and KML format. BAKOSURTANAL have built a data-based mapping system that connects the data with the provincial BAPPEDA. This system is called Geografis Marine Resource Information System – Marine and Coastal Resource Management Project (GMRIS-MCRMP). This Open Source-based systems includes application to upload, edit and display data that is part of the spatial data catalog of BAKOSURTANAL which is located at the Central Survey of Natural Sea (PSSDAL) and this system can be accessed on http://pssdal.bakosurtanal.go.id. BAKOSURTANAL specifically has provided spatial data through WMS. The aim of this research is to create a mapping system that can integrate spatial data format WMS and KML with Google Maps, and see the difference in time required to display maps between google maps and an old system, which displays the map using the framework chameoleon. The results of this research show that the mapping system which is integrated with Google Maps is able to display the spatial data layer format WMS and KML. With google maps, mapping systems are relatively faster in displaying a map composition. Keywords: Web Map Service, Keyhole Markup Language, Google Maps, GIS, Map.
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Judul: Leukemia pada kucing
Abstrak: Leukemia pada kucing adalah suatu penyakit yang sangat patogen, disebabkan oleh sejenis virus. Virus ini dikenal sebagai Feline Leukemia Virus atau FeLV. FeLV ini oleh beberapa ahli dikatakan hanya bersifat ganas pada hewan kucing. Penularannya bisa secara horizontal maupun congenital. Kucing pada semua tingkat umur dapat terserang oleh FeLV ini. Khusus pada bentuk "thymic leukemia", virus ini hanya menyerang anak-anak kucing berumur diba- wah 1 tahun. Kucing-kucing liar atau yang tidak terpeli- hara jarang sekali terinfeksi FeLV. Selain dari serangan virus FeLV itu sendiri, maka penyakit leukemia ini bisa disebabkan oleh beberapa fak- tor yang sudah ada dalam tubuh hewan dan sangat menunjang perkembangan penyakit ini, yaitu antara lain tumor, agen toksik, cedera oleh kecelakaan dan gangguan hemopoiesis. FeLV menyerang sel-sel darah dalam tubuh hewan se- hingga pembentukan darah berjalan tidak normal. Terlihat sel-sel darah yang belum dewasa sudah beredar dalam sir- kulasi darah. Bentuk dan jumlahnya tidak lagi seimbang dalam tubuh hewan kucing tersebut. Gejala klinis antara lain kekurusan, ikterus, anemia, lemah, anoreksia, dyspnoe, sulit menelan, batuk, dan membran mukosa pucat. Selain itu kelenjar pertahanan tubuh juga membengkak, kemudian terjadi hepatomegali, spleenomegali dan pembengkakan pada ginjal. Terbentuk massa tumor pada beberapa tempat. Secara biopsy pada sumsum tulang akan terlihat be- berapa perubahan. Sumsum tulang berwarna merah tua atau abu-abu. Konsistensinya lunak dan terdapat banyak sekali memproduksi sel darah putih. Melalui gambaran darah leukemia ini lebih mudah didiagnosa. Jumlah retikulosit rendah sekali. PCV 8-15%, hemoglobin menurun, sel darah putih (WBC) meningkat, lim- fosit meningkat, Alfaglobulin juga ada peningkatan, dan banyak eosinofil yang belum dewasa beredar dalam darah…dst
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