Judul: Pengaruh naungan dan pemupukan MgSO4.H2O terhadap produksi antosianin daun dewa (Gynura pseudochina (L.) DC)
Abstrak: Daun dewa merupakan tanaman obat yang banyak manfaatnya karena mengandung senyawa bioaktif antara lain golongan flavonoid. Antosianin termasuk golongan flavonoid yang dapat berfungsi untuk mengobati beberapa jenis penyakit khususnya tumor atau kanker pada manusia. Tanaman daun dewa mengandung berbagai senyawa kimia, antara lain saponin, flavonoid, minyak atsiri, dan antikoagulan. Oleh karena itu daun dewa mempunyai banyak kegunaan dan salah satunya adalah untuk mengatasi stroke. Cahaya merupakan faktor penting bagi pertumbuhan dan perkembangan tanaman, karena selain berperan dominan pada proses fotosintesis, juga sebagai pengendali, pemicu dan modulator respon morfogenesis khususnya pada tahap awal pertumbuhan tanaman. Spektrum cahaya yang dibutuhkan tanaman berkisar antara panjang gelombang 400-700 nm, yang biasa disebut photosynthetically active radiation (PAR). Disamping pengaturan intensitas cahaya (naungan) untuk mendukung pertumbuhan di lapang, pemberian unsur hara melalui pemupukan sangat penting untuk mekanisme produksi bioaktif (flavonoid/ antosianin) pada tanaman daun dewa. Magnesium dan sulfur yang merupakan unsur hara yang akan dicobakan pada penelitian ini memiliki peran spesifik pada mekanisme produksi senyawa flavonoid. Sulfur dalam bentuk SO4 2- merupakan elemen esensial dalam sintesis protein dan produksi senyawasenyawa metabolit sekunder dalam tanaman seperti flavonoid dan terpenoid, sedangkan magnesium dapat membentuk senyawa cianidin Mg-compleks yang merupakan salah satu aglikon antosianin. Penambahan kandungan Mg dalam tanah dapat dilakukan dengan pemberian pupuk Mg yaitu kieserit (magnesium sulfate/ MgSO4.H2O) dengan kandungan 29% Mg dan 23% S. Penentuan dosis magnesium dan sulfur yang tepat untuk meningkatkan kandungan flavonoid daun dewa sangat penting untuk diketahui.
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Judul: Isolasi Komponen Bioaktif Flavonoid dari Tanaman Daun Dewa (Gynura pseudochina (Lour) DC)
Abstrak: This research was including of isolation of flavonoid component from leaf and rhizoma of daun dewa plant, followed by bioassay test of larvae mortality of Artemia salina Leach and antikhamir to Saccharomyces cerevisiae. Extraction process of antocyanin flavonoid was done by maceration using HCl in MeOH solvent, whereas another flavonoid was done maceration too, but with two steps, first, using MeOH – H2O (9:1) and second, using MeOH – H2O (1:1). Filtrate obtained from these steps was collected together and dried using rotavapour. Extract that obtained from this process was partitied using n-hexan, chloroform, diethylether, ethylacetic and n-buthanol solvent, respectively. Its residue was soxhletated using petroleum ether and methanol. The existency of flavonoid was traced by phytochemical test, its bioavailabiolity was traced by toxicity test using A. salina Leach larvae (BSLT test) and antikhamir activity test to Saccharomyces cerevisiae with spectrometer UV-Vis and FTIR, GC-MS and HPLC. The result of phitochemical test of fresh leaf extract of daun dewa plant could not detect the anthocyanin flavonoid group. The result of BSLT test of leaf powder extract showed that buthanol fraction has the highest value of LC50 = 832.12297 ppm, in rhizoma powder extract, the ethylacetic showed the highest value of LC50 was 723.44205 ppm, but in those both extract did not show antikhamir activity to S. cerevisiae khamir. Separation of buthanol fraction was using TLC preparative with silica gel 60 F254 as a stationer phase and BAW as a mobile phase. It was resulted 7 fractions. Fraction 4 and 7 had LC50 value 7.80408 and 208.51563 ppm, respectively. The result of structure identification of fraction 4 and 7 with spectrometer UV-Vis and FTIR gave a clue that fraction 4 and 7 could be presumed contain of flavonoid group compound and these fractions had functional group such as OH, C=O ketone, C=C aromatic and C-O. The results of GC and HPLC showed fraction 4 and 7 obtained was not pure. From the result of HPLC analysis, the content of quercetine in fraction 4 was 2.7458 mg/g.
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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