Judul: Effect of Solvent in Continuous Shaking Extraction (CSE) Using Temu Ireng (Curcuma aeruginosa Roxb) on Total Terpenoids and Antioxidants Capacity.
Abstrak: Temu ireng (Curcuma aeruginosa Roxb) adalah salah satu ta man obat na di Indonesia yang memiliki manfaat sebagai antioksidan. Manfaat ini dikarenakan adanya kandungan berbagai jenis metabolit sekunder salah satunya senyawa terpenoid. Pemilihan metode dan jenis pelarut dalam proses ekstraksi penting agar senyawa metabolit sekunder dapat diteliti. Penelitian ini bertujuan menentukan jenis pelarut terbaik berdasarkan kadar total terpenoid dan kapasitas antioksidan rimpang temu ireng. Rimpang temu ireng diekstraksi dengan metode continuous shaking extraction (CSE) dengan pelarut n-heksana, aseton, heksan:aseton (1:1), dan heksan:etil asetat (1:1). Hasil ekstraksi diukur kadar total terpenoid dan kapasitas antioksidan menggunakan 2,2-diphenyl-1-picrylhydrazyl (DPPH) dan Ferric-reducing Antioxidant Power (FRAP). Hasil penelitian menujukkan kadar total terpenoid tertinggi diperoleh oleh pelarut heksan:aseton senilai 1471,58, Temu ireng (Curcuma aeruginosa Roxb) is one of the medicinal plants in Indonesia which has benefits as an antioxidant. This research aimed to determine the best type of solvent based on total terpenoid content and antioxidant capacity of temu ireng rhizomes. Temu ireng rhizomes were extracted using continuous shaking extraction (CSE) method with the solvents n-hexane, acetone, hexane:acetone (1:1), and hexane:ethyl acetate (1:1). The extraction were measured for total terpenoid content and antioxidant capacity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Ferric-reducing Antioxidant Power (FRAP). The research showed that the highest total terpenoid content was obtained by hexane:acetone solvent worth 1471.58
Keyword: antioksidan, pelarut, temu ireng, terpenoid, antioxidant, solvent, temu ireng, terpenoid

Judul: Optimization of Phenolic Active Biomolecules Extraction and Antioxidant Activity of Temu Ireng Rhizome (Curcuma aeruginosa Roxb.)
Abstrak: Curcuma aeruginosa Roxb. adalah salah satu tanaman obat yang mengandung senyawa fenol yang berpotensi sebagai antioksidan. Penelitian ini bertujuan menentukan kondisi optimum ekstraksi rimpang temu ireng yang berpengaruh terhadap rendemen ekstrak, kandungan total fenolik dan aktivitas antioksidan. Optimasi ekstraksi rimpang temu ireng dengan metode maserasi dilakukan berdasarkan half factorial design (2(k-1)) menggunakan dua level (level tinggi dan rendah) dan lima faktor . Faktor-faktor tersebut meliputi pH (2 dan 6), suhu (30°C dan 80°C), konsentrasi etanol (20% dan 80%), waktu (30 dan 300 menit), dan rasio cairan terhadap padatan (10 dan 100 mL/g). Penelitian menunjukkan bahwa konsentrasi etanol berpengaruh sangat nyata (p<0.0001) terhadap kadar total fenolik dan antioksidan dengan nilai paling tinggi yaitu 37 mg GAE/g ekstrak dan 133.725 μg/mL pada konsentrasi etanol 80%. Kondisi ekstraksi yang optimum berdasarkan analisis dengan program Design Expert yaitu pada pH 2, konsentrasi etanol 80%, suhu 30oC, waktu inkubasi 30 menit, dan rasio cairan terhadap padatan yaitu 100 mL/g.
Keyword: Bogor Agricultural University, Institut Pertanian Bogor, IPB, Antioxidant, C. aeruginosa Roxb, extraction, half factorial design, phenolic, Tanaman obat, Respon rendemen ekstrak, Optimasi kondisi, Ekstraksi

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