Judul: Aktivitas Antioksidan, Kadar Fenolik, dan Flavonoid Tumbuhan Suruhan (Peperomia pellucida L. Kunth)
Abstrak: Suruhan (Peperomia pellucida L.Kunth) is the bush had widespread in Indonesia and has efficacy as arthritis pain relief, anticancer, and antibacterial. The aim of this study was testing the activity of suruhan’s herb extracts as natural antioxidants and measured the total phenolic and flavonoid content in suruhan. The sample used in the form of 70% ethanol extract and aqueous extract of the suruhan. The extract obtained by maceration method and tested antioxidants with DPPH method and then tested the content of total phenolic and flavonoid extracts and analyzed the correlation of these compounds to antioxidant activity. The yield of 70% ethanol extract was 20.43 ± 3.33% whereas the yield of aqueous extract was 10.03 ± 2.85%. Both of extract has produced the antioxidant activity of free radical DPPH capture. IC50 values of aqueous extract of 256.67 ± 21.65 ppm, followed by ethanol extract of 297.79 ± 17.75 ppm. Total phenolic content of aqueous extract was 755.79 ± 65.87 mgTAE/g and ethanol extract was 622.46 ± 179.43 mg TAE/g. Total flavonoid content of ethanol extract was 4.058 ± 0.352 mg QE/g and aqueous extract was 0.67 ± 0.352 mg QE/g extract for aqueous. The phenol content have linier correlation with their antioxidant activity but the flavonoid content didn’t have correlation with antioxidant activity.
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Judul: Antioxidant, HMG-CoA Reductase Ihibition activity, and Chemical Compound Identification of Surian (Toona sinensis) Leaves Extract.
Abstrak: Surian (Toona sinensis) is forest plant that are widespread in Asia. This plant only used and known as a comodity for carpentry in Indonesia but in other nation surian is known as spices and traditional medicine because of its natural antioxidant potential. The objective of this study was assayed total phenolic content, total flavonoids content, antioxidant activity, HMG-CoA reductase inhibition activity and to analyze chemical compound from Surian leaves extract. Surian leaves were extracted by water and ethanol solvent. Water extraction was conducted by reflux in 90 oC then ethanol extraction was conducted by maceration, which is through various concentration 70%, 80%, 90%, and 96% of ethanol. Total Phenolic content was determined according to the Folin–Ciocalteu method using miligram of gallic acid equivalent and total flavonoid content was evaluated using aluminium chloride by compared with quercetin standard. Antioxidant activity of the water and ethanol extracts was evaluated using DPPH radical scavenging method. Inhibition of HMG-CoA reductase was assayed in vitro using single concentration inhibition with atorvastatin as comparison. Total phenolic and flavonoid content of ethanol 90% extract and ethanol 96% extract had higher amount than the other. The ethanol 96% extract had the strongest DPPH inhibition conccentration 50% (IC50), which is 3.38 μg /mL while ascorbic acid is 3.90 μg /mL as a comparison. The ethanol 96% extract also had highest inhibition HMG-CoA reductase activity which is 79.13% and this activity strongest in water fraction from this extract with inhibition 91.49% while atorvastatin as a comparsion is 92.45%. Antioxidant and inhibition ezyme activity had strong corelaltion with total flavonoid content. Chemical compound by LC-MS assay mostly are counted in the flavonoids group.
Keyword: Antioxidant, Flavonoids, HMG-CoA reductase, Toona sinensis

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