Judul: Penurunan Bilangan Kappa Pulp Organocell dari Beberapa Jenis Kayu Hutan Tanaman Industri
Abstrak: Permintaan pasar akan pulp dan kertas dari waktu ke waktu cenderung meningkat. Hal ini seiring dengan pertumbuhan penduduk dan perkembangan teknologi. Pada tahun 1998/1999 diharapkan kapasitas produksi industri pulp national dapat mencapai 4.387.900 ton (ibnusantoso, 1995).
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Judul: Penurunan bilangan kappa pulp alcell dari beberapa jenis kayu hutan tanaman industri
Abstrak: Umumnya industri pulp kertas di Indonesia menggunakan proses kimia terutama Proses Kraft karena dapat mengolah semua jenis kayu, sifat fisik lembaran pulp yang dihasilkan sangat tinggi dan pemulihan kembali bahan kimia pemasak mudah. Selain kelebihan-kelebihan itu, Proses Kraft memiliki kelemahan-kelemahan seperti menimbulkan pencemaran udara akibat timbulnya H₂S dan CH,SH, serta membutuhkan khlor lebih banyak untuk pemutihan, Salah-satu alternatif untuk menghilangkan kelemahan- kelemahan itu adalah dengan mengembangkan proses Alcell, karena mempunyai beberapa keuntungan terutama rendemennya yang tinggi. Namun demikian, hingga saat ini masih terdapat kelemahan-kelemahan dalam pembuatan pulp dengan proses Alcell yaitu tingginya bilangan kappa dan opasitas serta rendahnya indeks sobek dari lembaran pulp. Dari kelemahan yang ada maka perlu dilakukan modifikasi kondisi pemasakan khususnya rasio larutan-serpih kayu yang dilanjutkan dengan pencucian dengan variasi aseton-air sehingga diperoleh bilangan kappa pulp yang lebih rendah. Tujuan penelitian ini adalah untuk memperoleh bilangan kappa yang lebih rendah untuk jenis kayu Paraserianthes falcataria (L) Nielsen, Acacia mangium Willd dan Eucalyptus urophylla Blake dengan modifikasi rasio larutan-serpih kayu yang dilanjutkan dengan pencucian variasi aseton- air serta mengetahui rendemen, sifat fisik dan sifat optik pulp setelah pemasakan yang dilanjutkan pencucian dengan variasi aseton-air. ...
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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