Judul: Identifikasi emisi gas rumah kaca dan analisis serapan C-Organik pada berbagai sistem pengelolaan tanaman padi
Abstrak: Pemanasan global igloba! +i~aiaiiiiSmj eiupakaii permasalahan lingkdngan yang memberikan pengaruh nyata dalam kehidupan. Hal ini disebabkan karena meningkatnya konsentrasi gas rumah kaca (CO2, CFCs, N20, CH4) di atmosfer bumi. Seiania h r i n wak?u 2 abad teiah terjadi peningkatan ~uiiu atmosfer bumi yang telah mengakibatkan beberapa bencana alam. Akibat lain pemanasan global adalah naiknya pertnukaan air laut, punabriya bebesapa spesies karena tidak mampu beradaptasi terhadap perubahan ikiim. Kementrian Negara Lingkungan Hidup (1999) memprediksi bahwa total emisi GRK (CO2, CFCs dan N20) di Indonesia berturut-turut sebesar 543.3 Tg, 4.69 Tg dan 0.061 Tg per tahun dan konsentrasi gas-gas tersebut akan mengalami peningkatan seiring dengan peningkatan kegiatan manusia untuk memenuhi kebutuhan tanpa adanya teknologi atau cara untuk menekan emisi tersebut. Konsentrasi GRK di atlllostfer terus mengalami peningkatan, konsentrasi gas C& dan N2O saat ini mencapai 1852 ppbv dan 319 ppbv sedangkan konsentrasi gas COZ 375 ppmv.
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Judul: Distribusi Spasial C-Organik Tanah di Wilayah Sekitar Puncak dan Cianjur
Abstrak: Dewasa ini permasalahan lingkungan hidup telah mendapat perhatian yang cukup besar di hampir semua negara, baik di negara berkembang maupun negara maju. Salah satunya adalah permasalahan pemanasan global. Naiknya intensitas efek rumah kaca yang disebabkan oleh gas-gas rumah kaca (GRK) akan menyebabkan pemanasan global. Adapun GRK yang dianggap paling berkontribusi terhadap gejala pemanasan global adalah CO2, CH4, N20, NOX, CO, PFC dan SF6. Dari GRK tersebut, CO2 memberikan kontribusi terbesar terhadap pemanasan global yaitu 82 % sementara CH4 memberikan kontribusi 15 %. GRK yang penting adalah CO2 yang berasal dari respirasi, pembusukan, pembakaran bahan organik dan pembakaran bahan bakar fosil.
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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