Judul: Efektivitas fiksasi N2 dan oksidasi metan kultur campuran bakteri metanotrof asal sawah
Abstrak: Sebagian besar emisi CH4 di lahan sawah yang tergenang diproduksi oleh bakteri metanogen dan sebanyak 80 % dari CH4 tersebut dioksidasi oleh bakteri metanotrof. Selain kemampuan mengoksidasi metan, metanotrof juga memiliki kemampuan memfiksasi nitrogen. Empat isolat metanotrof dengan kemampuan fiksasi nitrogen (BGM 1, BGM 3, BGM 5, dan BGM 9) masing-masing dikombinasikan dengan isolat metanotrof yang memiliki aktivitas oksidasi metan tinggi (SKM 14) untuk mendapatkan formulasi metanotrof yang tinggi aktivitas fiksasi nitrogen dan oksidasi metan-nya. Kemampuan fiksasi nitrogen diukur dari kadar amonium yang diakumulasikan dalam medium pertumbuhannya dan aktivitas reduksi asetilen (ARA). Akumulasi amonium tertinggi dicapai oleh kultur BGM 1 untuk kultur tunggal (1,86 μM amonium), dan kultur BGM 3/BGM 9 untuk kultur kombinasi (4,905 μM amonium). Aktivitas nitrogenase tertinggi ditunjukkan oleh kombinasi BGM 1/SKM 14 (11,27 μmol/ml kultur/hari), sedangkan aktivitas oksidasi metan tertinggi dicapai oleh kultur campuran BGM 5/BGM 9 (18,20 ppm/ml kultur/hari).
Keyword: Metan, Bakteri metanotrof, ARA, Fiksasi nitrogen, Oksidasi metan, Bogor Agricultural University, Institut Pertanian Bogor, IPB

Judul: Aktivitas fiksasi nitrogen dan oksidasi metan kultur campuran bakteri metanotrof pada lumpur sawah
Abstrak: Metanotroph bacteria are methane oxidizing bacteria. Besides, type II and type X of methanotrophic bacteria were also able to fix nitrogen using nitrogenase enzyme. This reasearch was conducted to test the activity of nitrogen fixation and methane oxidation of five isolates of methanotropic bacteria i.e. BGM 1, BGM 3, BGM 5, BGM 9, and SKM 14 which combined with one another. Seven combinations (SKM 14/BGM 1; SKM 14/BGM 3; SKM 14/BGM 5; SKM 14/BGM 9; BGM 9/BGM 1; BGM 9/BGM 3; BGM 9/BGM 5) were cultured and inoculated into NMS medium mixed with slurry of mud, then the activity of methane oxidation, nitrogen fixation and nitrogenase enzyme activity was tested. The highest accumulation of ammonium in the mud sterile treatment (35.489 μM) was higher than that of in non-sterile mud treatment (26.617 μM). Formulation 6 (BGM 9/BGM 3) in sterile mud treatment and formulation 4 (SKM 14/BGM 9) in non-sterile mud treatment has the highest nitrogenase enzyme activity, it was 5,16 mmol/h/ml culture and 75,85 mmol/h/ml culture respectively. Formulation 1 (SKM 14/BGM 1) and formulation 2 (SKM 14/BGM3) had the higest activity of methane oxidation in sterile and non sterile mud treatment i.e. 17428 and 16759 ppm /ml culture /day respectively.
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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