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: Pendugaan Emisi Gas Rumah Kaca (CO2) Akibat Kebakaran Hutan dan Lahan pada Berbagai Tipe Tutupan Lahan di Provinsi Sumatra Selatan Tahun 2000-2009
Abstrak: Kebakaran hutan merupakan suatu permasalahan serius dan berpengaruh terhadap keseimbangan hutan yang berdampak sangat merugikan baik segi ekologis, ekonomi maupun politik. Oleh karena itu, diperlukan informasi mengenai kejadian kebakaran hutan dan lahan berdasarkan sebaran titik panas (hotspot) beserta emisi karbondioksida yang dihasilkannya, terutama di daerah yang rawan kebakaran hutan dan lahan, salah satunya Provinsi Sumatra Selatan. Tujuan dari penelitian ini adalah menghitung sebaran titik panas (hotspot) sebagai penduga terjadinya kebakaran hutan dan lahan di Provinsi Sumatra Selatan, menghitung estimasi luas area terbakar melalui sebaran titik panas (hotspot), dan menghitung estimasi emisi karbondioksida (CO2) yang dihasilkan dari luas area terbakar berdasarkan penutupan lahan yang berbeda. Penelitian ini dilakukan pada bulan Juli-September 2012 di Laboratorium Kebakaran Hutan, Departemen Silvikultur, Fakultas Kehutanan, Institut Pertanian Bogor. Data yang digunakan adalah data hotspot MODIS dari FIRMS, data curah hujan dari Badan Meteorologi Klimatologi dan Geofisika (BMKG), dan peta tutupan lahan Sumatra Selatan dari RSPO. Hasil analisis menunjukkan bahwa luas area terbakar terbesar di Provinsi Sumatra Selatan terdapat pada lahan pertanian tanah kering bercampur semak yang memiliki luas terbakar masing-masing sebesar 6.172 ha (2000),61.836,81 ha (2005), dan 127.259,53 ha (2009). Emisi CO2 terbesar terdapat pada pertanian tanah kering bercampur semak yaitu masingmasing sebesar 52.475,73 ton (2000), 524.417,17 ton (2005), 1.071.972,41 ton (2009) yang terdapat di tanah mineral, dan emisi CO2 terbesar akibat perubahan penutupan lahan terdapat pada perubahan pertanian tanah kering bercampur semak masing-masing sebesar 3.078.899,73 ton (44,52%) dan 20.443.299,85 ton (50,60%).
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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