Judul: Correlation between antioxidant activity of synthetic zeolites pillared titanium dioxide and iron (III) oxide with adsorption DPPH
Abstrak: Penyakit degeneraif akibat berlebihnya radikal bebas di dalam tubuh merupakan penyebab kematian tertinggi di dunia. Radikal bebas dalam tubuh mengakibatkan penuaan dini dengan merusak jaringan lemak yangberada di bawah kulit sehingga menghilangkan kekencangan kulit dan kulit menjadi keriput.Salah satu cara untuk menanggulangikelebihan radikal bebas adalah dengan menambahkan antioksidan alami pada produk farmasi dan bahan pangan. Zeolit merupakan salah satu material yang berpotensi sebagai antioksidan. Zeolit bekerja sebagai antioksidan dengan cara memerangkap radikal bebas dalam strukturnya sehingga radika bebas menajdi tidak aktif dan aman dihilangkan dari tubuh. Kinerja zeolit sebagai antioksidan dapat ditingkatkan dengan memilar zeolit dengan oksida logam misalnya TiO₂ atau Fe₂O₃.
Keyword: DPPH, Fe2O3, Methylene Blue, Synthetic zeolite type A and TiO2

Judul: Potensi Zeolit Alam Sebagai Antioksidan
Abstrak: Zeolite is an aluminosilicate mineral which are three dimensional frameworks in its structure, has cavities and channels connected to each other creating wide surface so that effective as an adsorbent. Besides, zeolite has negative charge, which can interact with charged compounds or molecules such as 1,1-diphenyl-2-picrylhydrazyl (DPPH). The aim of this research is to measure the activity of Indonesian natural zeolites from Banten, Lampung, Sukabumi, and Tasikmalaya to scavenge DPPH free-radical. Antioxidant activity test against DPPH performed on the untreated zeolite, temperature-activated zeolite, and acid-activated zeolite. The highest antioxidant activity was shown by Sukabumi zeolite, which was 85.56% when activated at 100 °C and 65.56% when activated with 1 M HCl. The results of scanning electrone microscopy and X-ray diffraction analysis showed that zeolites from Banten, Lampung, Sukabumi, and Tasikmalaya are clinoptilolite typ
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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