Judul: Pemrofilan Rimpang Temulawak Menggunakan Kromatografi Gas-Spektroskopi Massa
Abstrak: Penelitian ini bertujuan mengidentifikasi metabolit pada rimpang temulawak dan mendiskriminasi penyebaran rimpang temulawak dari 5 daerah sentral produksi di Jawa: Bogor, Karanganyar, Sukabumi, Ngawi, dan Wonogiri. Sampel diekstraksi dengan SPME (ekstraksi mikro fase padat) kemudian dianalisis menggunakan GC-MS (kromatografi gas-spektroskopi massa). Senyawa yang berhasil diidentifikasi dan dikonfirmasi untuk daerah Bogor, Karanganyar, Sukabumi, Ngawi, dan Wonogiri berturut-turut sebanyak 36, 40, 44, 44, 47 senyawa dengan komponen dominannya adalah α-Cedrene (18-21%), α-Curcumene (15-19%), Xanthorrhizol (6-9%), dan Germacrone (5-7%). Metabolit yang diduga sebagai penanda adalah α-Cedrene dan β–Sesquiphellandrene. Pengujian aktivitas antioksidan dengan metode DPPH (2,2-diphenyl-1-picrylhydrazil) terhadap ekstrak etil asetat rimpang temulawak membagi sampel menjadi 4 kelompok, sedangkan diskriminasi rimpang temulawak dari asal geografis berbeda menggunakan PCA (analisis komponen utama) membagi sampel menjadi 3 kelompok. Oleh karena itu, komposisi metabolit rimpang temulawak tidak dapat dikaitkan dengan aktivitas antioksidannya.
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Judul: Studi Metabolomik Rimpang Temulawak dari Berbagai daerah Menggunakan Kromatografi Gas-Spektometri Massa
Abstrak: Temulawak (Curcuma xanthorriza) merupakan tanaman obat yang mempunyai aktivitas sebagai antioksidan, antirematik, antihepatotoksik, antibakteri, dan antiinflamasi. Tujuan penelitian ini adalah membuat profil metabolit rimpang temulawak dengan kromatografi gas-spektrometri massa dan melakukan diferensiasi rimpang temulawak yang berasal dari 5 daerah yang berbeda menggunakan metode analisis komponen utama (PCA), serta menjelaskan mutu rimpang temulawak berdasarkan sifat bioaktivitasnya (toksisitas). Hasil penelitian menunjukkan bahwa keragaman senyawa metabolit rimpang temulawak dari Bogor, Karanganyar, Sukabumi, Sragen, dan Wonogiri berturut-turut mempunyai komposisi sebanyak 70, 70, 57, 66, dan 68 senyawa dengan 4 komponen dominan yang sama, yaitu α-kurkumena, α-sedrena, xantorizol, dan germakron. Analisis PCA menggunakan 2 komponen utama, yaitu PC 1 = 60% dan PC 2 = 30%. Ekstrak rimpang temulawak yang berasal dari daerah Bogor, Karanganyar, dan Sragen mempunyai tingkat toksisitas yang lebih tinggi sehingga mutu rimpang temulawak lebih baik daripada ekstrak dari daerah Wonogiri dan 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