Judul: Pengaruh Kebijakan Dalam Upaya Pengendalian Kebakaran Hutan dan Lahan Terhadap Penurunan Emisi Gas Rumah Kaca
Abstrak: Global warming and climate change occurs due to an increasing of concentrations of greenhouse gases. Indonesian forest fires and land policy has not been able to reduce the greenhouse gas emissions, so that condition will have an impact to global warming and climate change. The main question about government's decision regarding this matter are effectiveness of the policies. The purpose of this study is 1) to reviewing presence the government’s decision in reduce Greenhouse Gas Emissions (GGE) in the period 2005-2012 that accompanied the policy control of forest fire and land; 2) The government's commitment to reduce Greenhouse Gas Emissions (GGE) due to fire forest and land. Primary and secondary data was used in this study. Primary data obtained by interviews, while secondary data obtained by desk study of Ministry of Forestry and the Ministry of Environment documents. Secondary data were analyzed using descriptive analysis. In this study also conducted statistical tests, which is correlation test, to determine the correlation between forest hotspot and the amount of forest fires. Correlation between hotspot with the amount of forest fires in Indonesia by year 2010-2012 was 51.03%, while in 11 Indonesian province namely, Sumatera Utara, Riau, Kepulauan Riau, Jambi, Sumatera Selatan, Kalimantan Barat, Kalimantan Tengah, Kalimantan Selatan, Kalimantan Timur, Sulawesi Selatan, dan Sulawesi Barat of 61.25%. The correlation test shows a positive correlation between hotspots with widespread forest fires. Secondary data analysis of the results showed that the government's commitment to reduce the greenhouse gas emissions, mainly from forest fires is counterproductive. It shows that the trends of hotspot in Indonesia was increased by year 2010-2012. The increasing of hotspot resulted to the amount of forest fire. These fact lead the increasing greenhouse gas emissions amount released into the atmosphere. This means that the government policies implementation does not reach the objectives. This study are expected to provide a solution for of forest fire policy problems, particularly in reducing greenhouse gas emissions programs through Indonesian government policies.
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Judul: Pendugaan Emisi CO2 sebagai Gas Rumah Kaca Akibat Kebakaran Hutan dan Lahan pada Berbagai Tipe Penutupan Lahan di Provinsi Kalimantan Tengah Tahun 2000-2009
Abstrak: Forest fires became yearly severe problems in Indonesia. Central Kalimantan is one of Indonesia’s provinces that experienced severe forest fires in the last decade. Land conversion may be objected as one of trigger of forest fires that will produce carbon dioxide emissions. The purpose of this research is to calculate green house gas emission especially CO2 using hotspot data based on land use conversion at Central Kalimantan in the period 2000-2009. This research conducted between April and June 2012 at Forest Fires Laboratory, Silviculture Department, Faculty of Forestry, Bogor Agricultural University. The data used are MODIS hotspot data from Fire Information Resources Management System (FIRMS), precipitation data from Indonesian Meteorological, Climatological and Geophysical Agency (BMKG), and land cover map of Central Kalimantan from Roundtable on Sustainable Palm Oil (RSPO). The research results showed that primary forest decreased by 10% in 2009 while palm oil plantation increased more than 190% in 2009 compared to 2005. The numbers of hotspots are increasing from 2000 to 2009. The highest number of hotspots occurred in 2006 as 22,505 hotspot. The number of hotspots occurred on peat land (7,180) is found more than on mineral land (6,391). The increasing burned area from 2000 to 2009 correlates with the increasing of hotspots number on each land covers. Swamp shrubs have the highest burnt area of 113,609 ha, while the highest carbon emission is found from the land cover conversion of swamp shrubs into palm oil plantations as 801,764 tons. The highest carbon dioxide emission on mineral land in Central Kalimantan is found from shrubs in 2005 (459,427 ton). The highest carbon dioxide emission on peat land is found at disturbed swamp forest in 2005 (80,851 ton) and undisturbed swamp forest in 2009 (180,531 ton).
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Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm