Judul: Land Suitability Evaluation and Shrimp Culture Information System Development of PT. Indonusa Yudha Perwita
Abstrak: Utilization of GIS excess in land suitability analysis and Shrimp Culture Information System development of PT Indonusa Yudha Perwita (PT. IYP) are based on the absence of land suitability information and the lack of computerized data management. The study is designed to evaluate land suitability of PT. IYP’s ponds, to develop information system for aquaculture data management, and to analyze relation of land suitability of ponds and aquaculture operational success. The analysis of land suitability is performed by using multicriteria biophysical, and constraint factors like legislation to protect mangroves as buffer zone along coastline. Information system is built through requirement analysis stages, system design, and system development. The result of land suitability analysis is that 11.13 ha ponds area of PT. IYP located in moderately suitable class, and the rest 11.71 ha is very suitable. Due to government regulation in Keppres no. 32/ 1990, the moderately suitable area is designated as coastal greenbelt of mangrove. Shrimp Culture Information System of PT. IYP is able to provide efficiency, especially in time and data storage. Its capability in data processing, including, spatial comparison, temporal variation, and algebra application (FCR, SR, ADG, etc.), provides efficiency in evaluating shrimp culture activities. Lower yield from ponds locating on moderately suitable area than that from ponds in very suitable land is revealed as relation land suitability of PT. IYP to its production value.
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Judul: Development of Land Suitability Evaluation System for Coastal Aquaculture Using Artificial Neural Network and Geographical Information Systems (Case Study: Mahakam Delta, East Kalimantan)
Abstrak: Land suitability is the aptitude of given type of land to support a certain use. Land suitability is one of key factors for the sustainability of aquaculture system. It can be determined by using matching methods between land suitability criteria and land characteristics, such as topography, hydrography, climate, water characteristic, risk, land cover, and spatial plan aspects. Evaluation of land for aquaculture suitability can be reached using a parametric approach, which is implemented by using the distinguish land characteristics and combination of it. Parametric approach uses the numeric value, which classifies the land based on individual characteristics. The objectives of the research are to develop a land evaluation system on aquaculture suitability by using artificial neural network (ANN) and geographical information system (GIS) and to evaluate the performance of the new developed system as compared to GIS vector spatial analysis method. Four types of suitability were defined, i.e. highly suitable (S1), moderately suitable (S2), marginally suitable (S3) and not suitable (N). The new developed GIS model uses the raster format and ANN classifier. The performance of GIS model was then evaluated, and compared to the vector map overlay that used GIS spatial analysis features, including suitability distribution, covered area, processing speed and validity. The multilayer feedforward of the ANN with backpropagation learning algorithm was chosen to do the classification. GIS overlaid layer in form of spatial database was then converted into training dataset, validation dataset and prediction dataset. Training and validation dataset contains a pair of input and output, while the prediction dataset contains input data only. To compare the two methods, the Mahakam Delta-East Kalimantan were selected as a case study. Ten thematic map layers of land characteristic were involved in both methods, i.e.: water salinity, dissolved oxygen, water pH, soil texture, soil drainage, distance to rivers, pollution risk, land cover type, land use plan and annual rainfall intensity. Each feature of thematic map layers were classified and scored using 1 to 4 ranges from worst to best, respectively. The performance of ANN together with GIS was reliable, it includes the accuracy on training dataset of 97%, and validation of 96%. Distributions of each suitability of both methods are located on the same location in the study area. Area covered in the study area was 188,666.19 ha, consisting of 21,202.20 ha (11.24%) of 3 S1, 87,190.83 ha (46.21%) of S2, 6,958.26 ha (3.69%) of S3 and 61,251.12 ha of N. Only 0.19% of total area represents the “Unclassified Area” and 6.20% is “No Data”. Unclassified areas may be caused by less representative training dataset. “No Data” class represents the area that was not included in the data processing by raster data model. The research also proved that ANN together with GIS raster do the classification faster than vector spatial analysis.
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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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