Judul: Aktivitas Antioksidan Ekstrak Etanol Daun Murbei (Morus Alba L.) Dengan Metode Thiobarbituric Acid (Tba).
Abstrak: Daun murbei mengandung berbagai senyawa aktif yang berperan sebagai antioksidan. Ekstraksi daun murbei dengan etanol 65% menghasilkan kadar flavonoid dan fenolik tertinggi dibandingkan pelarut lain seperti aseton. Penelitian ini bertujuan menentukan konsentrasi optimum antioksidan ekstrak etanol daun murbei dengan mengukur konsentrasi malondialdehida menggunakan metode TBA, serta membandingkan aktivitas antioksidannya dengan α-tokoferol. Rendemen ekstrak yang diperoleh sebesar 24.52% dan rata-rata kadar air 7.26%. Hasil uji fitokimia positif pada flavonoid, tanin, steroid. Eugenol merupakan senyawa dengan kelimpahan terbesar mencapai 34.32% berdasarkan uji GC-MS. Hasil uji antioksidan menunjukkan bahwa ekstrak etanol daun murbei pada konsentrasi 125, 200, 500, dan 1000 ppm dapat menghambat pembentukkan MDA masing-masing sebesar 41.21%, 45.33%, 44.20% dan 36.00%. Potensi antioksidan daun murbei terbaik secara in vitro pada konsentrasi 200 ppm. Nilai inhibisi pada konsentrasi 200 ppm lebih rendah dibandingkan inhibisi α-tokoferol yang mencapai 62.06 %.
Keyword: antioksidan, eugenol, inhibisi, malondialdehida, murbei

Judul: Uji inhibisi enzim alfa glukosidase oleh ekstrak etanol daun murbei (Morus alba L) secara in vitro
Abstrak: Tanaman murbei adalah tanaman obat yang telah banyak digunakan dalam mengobati berbagai penyakit, termasuk diabetes. Inhibisi enzim α-glukosidase merupakan salah satu mekanisme mencegah terjadinya hiperglikemia postprandial. Penelitian ini bertujuan menguji kemampuan ekstrak daun murbei dalam menghambat enzim α-glukosidase secara in vitro. Ekstraksi menggunakan pelarut etanol 65% dengan perbandingan simplisia dengan pelarut 1:10. Hasil pengujian fitokimia menunjukkan ekstrak mengandung senyawa fitokimia flavonoid, tanin, dan steroid. Ekstrak mampu menghambat aktivitas enzim α-glukosidase dengan nilai IC50 sebesar 309.82 μg/mL. Persentase inhibisi dipengaruhi oleh konsentrasi ekstrak daun murbei (taraf uji 5%).
Keyword: mulberry, diabetes, Inhibition, α-glucosidase

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