Judul: Identifikasi Hutan Lahan Basah Menggunakan Citra ALOS PALSAR di Kalimantan Selatan
Abstrak: Wetland forest ecosystems have significant role in supporting human life, as a sources of water, food, biodiversity concervation, as well as a micro climate controller. Davies et al. (1995) noted that the extent of wetlands in Indonesia is about 38 million hectares. In addition, according to Komite Nasional Pengelolaan Ekosistem Lahan Basah (2004), Indonesia has about 40,5 million hectares of wetlands. While, according to Mulyani and Las (2008), Indonesia has about 40,2 million hectares of wetlands. The records of the extent of wetland in Indonesia is varied significantly due to different methods and data used. Thus, a development of remote sensing technology for monitoring of wetland ecosystems is required. In 2006, the government of Japan had launched ALOS (Advanced Land Observing Satellite) that carry a radar sensor called PALSAR (Phased Array Type L-band Shynyhetic Aperture Radar). ALOS PALSAR imagery is a new imagery and its interpretation methods has not been developed yet. The utilization of radar imagery data for forestry sector is also relatively undeveloped. The examination to evaluate the capability of the imagery is required. Considering the above mentioned matters, a study on the capability of ALOS PALSAR imagery for establishing identification techniques of forest wetland is required. The objective of the study is to evaluate the capability of ALOS PALSAR imagery for identifying wetland forest ecosystems. The research was conducted in Banjar, Barito Kuala, Banjarbaru, Banjarmasin, and Tanah Laut Regency, South Kalimantan Province. Identification of wetland forests was performed using ALOS PALSAR imagery, acquired in June of 2009 with 50 m resolution, with unsupervised classification method, separability analysis by transformed divergence (TD), and accuracy assesment. The hardware used in this study is a computer with Erdas Imagine Ver 9.1 and ArcView GIS Ver 3.2 softwares. This study found that wetland forest ecosystems that could be identified using ALOS PALSAR imagery with 50 m resolution include swamp forest with wet shrubs (bog) and mixed farms and also mangrove forest along with high shrubs. The accuracy evaluation showed that the accuracy for identification techniques of wetland forest are quite good having the overall accuracy and kappa accuracy are 73,49 % and 65,75 %, respectively.
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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: Analysis of M/G/1 Queue Model with Two Phases of Service and Bernoulli Feedback System
Abstrak: Model antrean M/G/1 dengan sistem feedback Bernoulli adalah model antrean dengan proses kedatangan mengikuti proses Poisson. Pada karya ilmiah ini dibahas sistem antrean M/G/1 dengan dua fase layanan. Setelah layanan pertama selesai, pelanggan dapat memilih untuk meninggalkan sistem dengan peluang ... dst, The M/G/1 queueing model with the Bernoulli feedback system is a queueing model with the arrival process following the Poisson process. In this manuscript M/G/1 queueing system with two phases of service is discussed. After the first service is completed, the customer can choose to leave the system with probability ... dst
Keyword: queue, Bernoulli, probability generating function, expected value