Judul: Pengaruh pelapisan permukaan papan partikel secara radiasi terhadap sifat-sifat permukaan papan partikel kayu karet (Hevea brasiliensis Muell. Arg.)
Abstrak: Penelitian ini bertujuan untuk mempelajari pengaruh pelapisan permukaan papan partikel dengan menggunakan radiasi berkas elektron dan ultraviolet terhadap sifat-sifat permukaan papan partikel kayu karet (Hevea brasiliensis Muell. Arg.). Papan Partikel yang digunakan diperoleh dari Pabrik Papan Partikel Suriakancana, Cibadak Sukabumi. Bahan pelapis dasar yang digunakan terdiri dari Laromer EA-81 + TPGDA + TiO₂ yang diperoleh dari PAIR-BATAN dan cat emulsi dengan nama dagang Vinylex yang didapat dari pasaran. Sedangkan bahan pelapis atas Laromer EA-81, Aronix 8060, Setacure AM 541, monomer TPGDA (Tripropilen Glikol Diakrilat) dan foto- inisiator Darocur 1173 dari PAIR-BATAN Jakarta. ...
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Judul: Pengaruh tingkat asetilasi dan perendaman panas selumbar terhadap sifat fisis dan mekanis papan partikel kayu karet (Hevea brasiliensis. Muell. Arg.)
Abstrak: Kebutuhan manusia terhadap kayu dari tahun ke tahun semakin meningkat, seiring dengan bertambahnya jumlah penduduk dan perkembangan teknologi, sehingga perlu pemanfaatan sumberdaya yang efisien. Salah satu usaha pemanfaatan bahan baku atau limbah kayu adalah dengan membuat papan partikel, karena dalam pembuatannya tidak memerlukan persyaratan bahan baku yang tinggi. Tetapi papan partikel masih memiliki kelemahan yang berarti, dalam hal stabilitas dimensinya yang rendah. Asetilasi terhadap selumbar dengan menggunakan bahan kimia anhidrida asetat adalah salah satu usaha untuk memperbaiki sifat-sifat papan partikel. Karena bahan tersebut harganya mahal, maka perlu penggunaan yang efisien. Penelitian ini bertujuan untuk mengetahui pengaruh tingkat penambahan anhidrida asetat dan perendaman panas terhadap sifat fisis dan mekanis papan partikel, serta untuk mengetahui penggunaan anhidrida asetat yang memadai. Papan partikel dibuat dari selumbar (flake) kayu karet berukuran kasar yang berasal dari Sasmaya T.o di Cibadak Sukabumi.
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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