Judul: Aktivitas Antibakteri Bunga Nangka Jantan (Artocarpus heterophyllus Lam.) Secara In Vitro
Abstrak: Diare yang disebabkan oleh infeksi bakteri telah diketahui dapat diobati oleh agen antibakteri. Bunga nangka jantan menurut pengalaman empiris masyarakat Temanggung, Jawa Tengah, dapat digunakan untuk meredakan diare. Penelitian ini bertujuan menguji aktivitas antibakteri bunga nangka jantan (Artocarpus heterophyllus Lam.). Prosedur penelitian meliputi uji kadar air, ekstraksi bunga nangka jantan, uji fitokimia, uji aktivitas antibakteri, dan uji konsentrasi hambat tumbuh minimum. Kontrol negatif yang digunakan adalah pelarut metanol, etil asetat, dan n-heksan, sedangkan kontrol positif yang digunakan adalah kloramfenikol. Hasil uji aktivitas antibakteri menunjukkan bahwa ekstrak metanol bunga nangka jantan lebih baik daripada ekstrak etil asetat, dengan rata-rata diameter zona hambat 5 mm terhadap E. coli dan 5.3 mm terhadap S. aureus, berspektrum luas, dan bakterisidal. Konsentrasi hambat tumbuh minimum terdapat pada ekstrak metanol sebesar 3.125 mg mL-1 .
Keyword: Antibacterial, Chloramphenicol, Male flower of jackfruit (Artocarpus heterophyllus Lam.), E. coli, S. aureus, Kloramfenikol, Ekstrak bunga nangka, Aktivitas antibakteri bunga nangka, Konsentrat hambat tumbuh

Judul: Aktivitas senyawa antibakteri akar tumbuhan anting-anting (Acalypha indica L.)
Abstrak: Anting-anting plants had been used by public traditionallly for curing various diseases like dysentry, diarrhea, malaria, and also as antibiotics. The research aimed to study the activity of compounds which had potential as antibactery in plant. The research was conducted activity of antibactery to Gram positif and negatif bacteria with four kinds bacteri are Staphylococus aureus, Bacillus subtilis, Escherichia coli dan Pseudomonas aeruginosa. The roots used were root extract from extraction of hexane solvent, ethyl acetate and methanol. The concentrations used was 200, 150, and 100 mg/ml for each solvents.
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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