Judul: Penapisan Ekstrak Daun Famili Zingiberaceae Sebagai Inhibitor Tirosinase Dan Antioksidan
Abstrak: Penapisan atas daun Zingiberaceae telah dilakukan sebagai inhibitor tirosinase dan antioksidan. Kadar total antosianin, klorofil, karotenoid, tanin, dan flavonoid ditentukan menggunakan metode spektroskopi. Metode penapisan antioksidan menggunakan 1,1-difenil-2-pikril hidrazil (DPPH) dan penapisan inhibitor tirosinase menggunakan substrat L-tirosina (monofenolase) dan L-DOPA (difenolase). Ekstrak metanol daun temulawak (Curcuma xanthorrhiza) lebih aktif sebagai antioksidan daripada ekstrak lainnya dengan nilai IC50 281.85 mg/L dan hubungannya dengan kadar tanin ialah 22.76%. Ekstrak etil asetat dari daun bangle hantu (Zingiber purpureum) memiliki aktivitas inhibisi monofenolase 82.86% dan hubungannya dengan kadar karotenoid ialah 52.02%. Ekstrak etil asetat daun temu putih (Curcuma zedoaria) memiliki aktivitas inhibisi difenolase 90.20% dan hubungannya dengan kadar flavonoid ialah 39%. Jadi, dari 10 daun spesies Zingiberaceae, temulawak lebih berpotensi sebagai antioksidan, sementara bangle hantu dan temu putih lebih berpotensi sebagai inhibitor tirosinase.
Keyword: antioksidan, inhibitor tirosinase, penapisan, Zingiberaceae

Judul: Pengaruh Jenis Pelarut terhadap Total Terpenoid dan Kapasitas Antioksidan Ekstrak Rimpang Temulawak  (Curcuma zanthorrhiza)
Abstrak: Temulawak (Curcuma zanthorrhiza) merupakan tanaman asli Indonesia mengandung antioksidan dan terpenoid yang mampu menangkal radikal bebas. Sampel rimpang temulawak diekstraksi dengan berbagai jenis pelarut diperlukan untuk mendapatkan senyawa bioaktif temulawak terbaik secara kuantitatif. Penelitian ini bertujuan menentukan pengaruh berbagai jenis pelarut ekstraksi terhadap total terpenoid dan kapasitas antioksidan rimpang temulawak. Sampel diekstraksi dengan gabungan metode sonikasi dan maserasi. Tahapan penelitian meliputi pengujian kadar total terpenoid rimpang temulawak, kemudian dilanjutkan pengujian kapasitas antioksidan dengan metode DPPH, CUPRAC, FRAP, dan ABTS. Hasil penelitian menunjukkan kadar total terpenoid terbesar dihasilkan oleh pelarut H (heksan p.a) sebesar 243.74 ± 8.13a mg UA/g DW dan kapasitas antioksidan terbesar dihasilkan oleh metode FRAP dengan pelarut aseton sebesar 131.25 ± 4.33a. Berdasarkan data dapat disimpulkan terpenoid bukan merupakan komponen utama senyawa antioksidan pada rimpang temulawak karena perbedaan pelarut yang dihasilkan antara data kapasitas antioksidan dan kadar total terpenoid., Temulawak (Curcuma xanthorrhiza) is a plant native to Indonesia that contains antioxidants and terpenoids which are able to ward off free radicals. Temulawak rhizome samples were extracted with various types of solvents to obtain the best bioactive compounds in curcuma quantitatively. This research aimed to determine the effect of various types of extraction solvents on the total terpenoids and antioxidant capacity of curcuma rhizomes. Samples were extracted by a combination of sonication and maceration methods. The research stages included testing the total terpenoid content of curcuma rhizomes, then continued with testing the antioxidant capacity using the DPPH, CUPRAC, FRAP, and ABTS methods. The results showed that the highest total terpenoid content was produced by the H solvent (hexane p.a) of 243.74 ± 8.13a mg UA/g DW and the largest antioxidant capacity was produced by the FRAP method with acetone solvent of 131.25 ± 4.33a. Based on the data, it can be concluded that terpenoids are not the main component of antioxidant compounds in curcuma rhizomes due to differences in the solvent produced between antioxidant capacity data and total terpenoid levels.
Keyword: curcuma, types of solvent, antioxidant, terpenoids

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