Judul: Penggunaan Pulp Kenaf (Hibiscus cannabinus) sebagai Bahan Baku pada Pembuatan Kertas Sigaret
Abstrak: Kertas sigaret adalah kertas yang digunakan sebagai pembungkus tembakau pada rolcolc. Kebutuhan kertas sigaret sangat tergantung dai-i perkembangan industri rokok. Dengan sernakin banyaknya industri roknk sekarang ini, tentunya aka!-!' meningkatkan kebutuhan kertas sigaret. Kertas sigaret yang digunakan sekarang ini kfbanyakan masih diimpor dari i u a v negeri atau kalauptin dihuat dl dalam negri pulp yang digunakan masih pulp impor.
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Judul: Pengaruh Alkali Aktif dan Suhu Pemasakan Terhadap Sifat-sifat Pulp Kenaf (Hibiscus cannabinus L) dengan Proses Soda dan Proses Sulfat
Abstrak: Di Indonesia pada saat ini industri pulp dan kertas sedang dikembangkan sebagai komoditi ekspor non migas andalan karena pangsa pasamya di dunia cukup tinggi. Hal ini didukung oleh potensi Indonesia yang cukup tinggi di dalam penyediaan bahan baku industri tersebut. Pada saat ini di Indonesia terdapt 16 pabrik pulp dengan kapasitas 3.905.600 ton dan 74 pabrik kertas dengan kapasitas 7.232.800 ton (APKI,1997). Sejalan dengan perkembangan industri pulp dari kertas di Indonesia, kebutuhan akan bahan baku berselulosa dirasakan semakin meningkat sehingga diperlukan suatu usaha penyediaan bahan baku yang cukup. Untuk memenuhi kebutuhan bahan baku industri pulp berserat panjang dalam negeri dicari alternatif bahan baku lain seperti non kayu mengingat penyediaan bahan baku terutama kayu daun jarum sangat terbatas. Adapun bahan baku pulp yang perlu dikembangkan dari non kayu yang mempunyai serat panjang salah satunya adalah kayu kenaf (Hibiscus cannabinus L ).
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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