Judul: Mangrove Classification on ASTER VNIR using Vegetation Indices and Neural Networks Study Case : Berau Delta, East Kalimantan.
Abstrak: ASTER with its VNIR sensor have the capability for mapping vegetation. With the resolution of 15m x 15m, this image should be able to classify mangrove is more details than Landsat TM with resolution of 30m x 30m. Based on this, algorithms was applied to explore the capability of this image for classifying mangrove. These are Standard Back Propagation Neural Network and some vegetation indices (DVI, NDVI, SR, and the modified of these algorithm by using Natural Color Composite : NCC-DVI, NCC-NDVI, NCC-SR). While, as study area, Berau Delta, East Kalimantan is chosen because there are still may found many species of mangroves. Each algorithm show different results, but almost all of them capable to classify mangrove into zone level, except modification of vegetation index algorithms. Standard Back Propagation Neural Network is not quite good for classifying mangrove, because it can generate pixels into lower number of classes. While, DVI, NDVI, and SR can classify mangrove into 4 class. Its rather low than Maximum Likelihood Supervised classification and ISODATA Unsupervised classification which produced 5 class. But, when modified vegetation index applied, it a different results. They can detect Nypa fruticans class clearly than other species. Even, by using NCC-NDVI and NCC-SR class Nypa still can differentiate into detailer condition. The specific condition of the area of study where high frequency of rain, may cause the amount of water content in the vegetation become increase. Since gives influence in low value of NIR reflectance and high reflectance of RED channel, the modified algorithm of vegetation indices using NCC applied, and show result better than standard algorithm of vegetation indices.
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Judul: Klasifikasi Mangrove Berbasis Objek dan Piksel Menggunakan Citra Satelit Multispektral di Sungai Kembung, Bengkalis, Provinsi Riau
Abstrak: Mangrove that generally found in coastal regions plays important roles such as (1) coastal protection from hurricane, tsunami, wind and wave, (2) spawning ground for many fishes and other faunas, (3) a place for recreational, (4) source of nutrients for organisms, and (5) source of wood. Recently, mangrove ecosystems in Kembung River, Bengkalis Island Riau Province tend to get pressure from antrophogenic. Protection and management of mangrove ecosystems needs to be a serious concern of various parties. Such efforts require data acquisition techniques and information mangrove spatially and accurately. Field data were collected in June and December 2012. Satellite imageries were used in this study consisted of Landsat 5 TM, Landsat 7 ETM +, Landsat 8 OLI, SPOT 6 multispectral, SPOT 6 panchromatic, ALOS PALSAR and SENTINEL-1. Pre-processing in the satellite imageries were applied including atmospheric correction, radiometric calibration, geometric correction, and spectral transformation. Field data observations and measurements were conducted on mangrove vegetation and land cover. Scheme development of mangrove community classification was conducted by using clusters and similarity percentage (SIMPER) analyses. Furthermore, the scheme was used to charactirized satellite images spectral reflectance by using spectral analysis. Satellite data were classified by using object-based approach which applied random forest algorithm. Object-based classification results was then compared to pixel-based classification technique which used maximum likelihood algorithm. The succesfull object-based classification then applied on magrove change detection in the study area. Kembung River mangrove community was assembled by 69 mangroves species which consists of 22 true mangrove species and 47 species of associate mangrove. Xylocarpus granamun, Rhizophora. apiculata, Lumnitzera. racemosa and Scyphiphora hidrophyllaceae were dominant species and always found in the study area compared with other species, for all strata. Based on standard criterias and guidelines for the determination of mangrove destruction which issued by the Minister of the Environment No. 201 of 2004, Mangrove at Kembung River was categorized as good and very dense mangrove ecosystem. Based on the composition of mangrove species, one level classification scheme was succesfully developed. The scheme consisted of 12 mangrove community classes, however most of the mangrove species belong to the two main classes of Rhizophora apiculata (Ra) composed of 33 samples and Xylocarpus granatum (Xg) composed of 93 samples Other 10 classes had limited sample number, therefore the 10 other classes were groupped into one class (La) that composed of 28 samples. Both classification techniques were able to identify all land cover classes and mangrove communities. Some misclassifications were still found to produce salt and pepper effects on both classifications, however, the random forest algorithm v could reduced such errors than the maximum likelihood algorithm. The best result of land cover classification using object-based and pixel-based classifications was obtained through input image layer M6. The object-based classification approach was better than pixel-based and it can improved the classification results by 1-24.5%. Change detection analyses showed that the mangrove area in Kembung River was relatively stable. For nearly two decades, we found mangrove loss about 197.2 ha, gain of 251.1 ha, and unchanged of 2904.9 ha. Changes in mangrove covers were generally caused by anthropogenic factors
Keyword: classification, Kembung River, mangrove, object-based, pixel-based

Judul: Penetapan Harga Jaminan Polis Asuransi Jiwa dengan Premi  Tahunan dan Opsi Surrender
Abstrak: Asuransi jiwa memberikan perlindungan pada tertanggung (pemegang polis) jika mengalami risiko finansial, dengan suatu perjanjian tertanggung harus membayar premi. Premi yang sudah terkumpul pada perusahaan asuransi dapat diinvestasikan, yang salah satu tempatnya adalah di pasar bursa. Perusahaan asuransi menawarkan suatu kontrak kepada pemegang polis yang disebut dengan kontrak partisipasi. Pada kontrak partisipasi risiko finansial dan keuntungan dibagi dengan pemegang polis dan biasanya keuntungan tersebut dimasukkan ke dalam cadangan polis pada tiap akhir tahun kontrak. Hal ini berarti secara tidak langsung perusahaan asuransi menyatakan penambahan pertanggungan, sehingga mengakibatkan perubahan benefit yang diterima oleh pemegang polis. Pada kontrak partisipasi ini, pemegang polis diberikan hak untuk mengakhiri kontrak (opsi surrender). Pada kontrak partisipasi asuransi jiwa endowmen terdapat opsi bonus (bonus option) yang penghitungan besar preminya dengan pendekatan tipe Eropa dan opsi surrender (surrender option) dengan tipe Amerika.
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