Judul: Perubahan Sifat Fisis dan Mekanis Lentur Dinamis Kayu Termodifikasi Panas Untuk Jenis Kayu Jabon dan Jati Akibat Pemaparan Alami.
Abstrak: Kayu merupakan bahan baku yang banyak kegunaan nya. Dalam penggunaan eksterior, sifat kayu dipengaruhi oleh banyak faktor. Modifikasi kayu menggunakan metode perlakuan panas diperlukan untuk meningkatkan sifat seperti perubahan warna, perubahan ketahanan secara biologis dan juga untuk meningkatkan stabilitas dimensi. Perlakuan panas secara umum menurunkan sifat mekanis dari kayu. Tujuan dari penelitian ini adalah untuk mengetahui perubahan sifat fisis dan mekanis lentur dinamis dari kayu yang termodifikasi panas akibat pemaparan secara alami. Kayu yang digunakan adalah jabon (Neolamarckia cadamba) dan jati (Tectona grandis) dengan perlakuan menggunakan 3 suhu berbeda (120 °C, 150 °C and 180 °C) dan 2 waktu yang berbeda (2 dan 6 jam). Hasil penelitian didapatkan bahwa sifat fisis dari kayu terjadi perubahan selama 10 bulan pemaparan, serta kelenturan dinamis (MOEd) kayu menurun drastis setelah 2 bulan pemaparan.
Keyword: modifikasi kayu, perlakuan panas, sifat fisis, sifat mekanis, pengujian non destructive

Judul: Sifat Mekanis Lentur dan Kuat Tekan Kayu Termodifikasi Panas untuk Jabon [Neolamarckia cadamba (Roxb.) Bosser] dan Jati [Tectona grandis Linn.f.].
Abstrak: Perlakuan pemanasan (heat treatment) dapat merubah sifat mekanis kayu. Perlakuan pemanasan merupakan salah satu alternatif modifikasi kayu yang ramah lingkungan. Tujuan dari penelitian untuk mengetahui pengaruh modifikasi panas terhadap sifat mekanis lentur dan kuat tekan terhadap kayu jabon [Neolamarckia cadamba (Roxb.) Bosser] dan jati [Tectona grandis Linn.f.]. Perlakuan pemanasan dilakukan dengan variasi suhu (120, 150 dan 180) °C untuk waktu (kontrol, 2 dan 6) jam. Sebelum diberi perlakuan pemanasan contoh uji dikeringkan menggunakan kipas (suhu ruang ±25 °C) dan experimental kiln (suhu 40 °C). Sifat mekanis yang diuji berupa lentur (MOE dan MOR) dan kuat tekan sejajar serat. Perlakuan pemanasan tidak berpengaruh nyata terhadap nilai MOE kayu jabon dan kayu jati. Perlakuan pemanasan cenderung menurunkan nilai kadar air kayu jabon dan jati.
Keyword: pengeringan, perlakuan panas, jabon, jati, lentur, kuat tekan

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