Judul: Molecular Docking of Compounds of Ethanol Extract of Temu Ireng Rhizome (Curcuma aeruginosa Roxb.) as Antioxidant and Anticancer.
Abstrak: Kanker merupakan salah satu jenis penyakit berbahaya yang mengalami peningkatan kasus setiap tahunnya. Radikal bebas merupakan penyebab mutasi gen yang dapat memicu kanker. Kanker akan berkembang tanpa terkendali karena terjadinya disregulasi siklus sel dan adanya senyawa pemicu proliferasi sel serta penghambat proses apoptosis. Pengobatan kanker dilakukan dengan memberikan inhibitor cyclin dependent kinase2 (CDK2) dan cyclooxygenase-2 (COX-2) untuk menghambat perkembangan kanker, serta inhibitor lipoxygenase (LOX) untuk menghambat pembentukan radikal bebas. Tanaman temu ireng diketahui memiliki potensi sebagai antioksidan dan antikanker. Penelitian ini bertujuan mengetahui interaksi molekuler antara senyawa dominan ekstrak etanol temu ireng dengan CDK2, COX-2, dan LOX sebagai reseptor. Jenis interaksi ligan dengan reseptor ditentukan melalui parameter energi afinitas (ΔG), konstanta inhibisi (Ki), jenis interaksi dan persentase binding site similarity (%BSS). Hasil penelitian menunjukkan bahwa senyawa uji gajutsulacton A memiliki potensi terbaik dalam menghambat CDK2. Senyawa uji cucumenol berpotensi sebagai inhibitor COX-2 tetapi tidak terdapat senyawa yang dapat menghambat LOX dengan baik sebagai antioksidan., Cancer is one type of dangerous disease that is increasing every year. Free radicals are the cause of gene mutations which can lead to cancer. Cancer will develop uncontrollably due to the dysregulation of the cell cycle and the presence of compounds which trigger cell proliferation and inhibit the process of apoptosis. Cancer treatment is carried out by giving cyclin-dependent kinase2 (CDK2) and cyclooxygenase-2 (COX-2) inhibitor drugs to inhibit cancer development, as well as lipoxygenase (LOX) inhibitor drugs for the formation of free radicals. The temu ireng plant is known to have the potential as an antioxidant and anticancer. This study aims to determine the molecular interaction between the dominant compound of temu ireng ethanol extract with CDK2, COX-2, and LOX receptors. The type of ligand interaction with the receptor was determined through the parameters of affinity energy (ΔG), inhibition constant (Ki), type of interaction, and percentage of binding site similarity (%BSS). The results showed that the test compound gajutsulacton A had the best potential in inhibiting CDK2. The test compound cucumenol may be a COX-2 inhibitor and there are no compounds that can inhibit LOX well as an antioxidant.
Keyword: Anticancer, Antioxidant, CDK2, COX-2, LOX

Judul: Efek Pemberian Ekstrak Etanol Temu Ireng (Curcuma Aeruginosa Roxb.) pada Proliferasi Sel Lestari Tumor THP1 dan A549 Secara In Vitro.
Abstrak: The use of plant extracts is one of alternative ways to heal tumor diseases. The purpose of this research is to study the effect of ethanol extract of temu ireng (Curcuma aeruginosa Roxb.) on proliferation of THP1 and A549 cell lines. The extract concentration used were 0 ppm (as a negative control), 12.5 ppm, 25 ppm; 37.5 ppm and 50 ppm, doxorubicin as a positive control, and the treatment were in three replications. All data were analyzed statistically by ANOVA and Duncan test. The results showed that inhibition activity of temu ireng ethanol extract on THP1 and A549 cell line proliferation were significantly different (p<0.05) than negative control. Inhibition activity were as higher as treatment dose and significantly different (p<0.05) between dose, except 25 ppm and 37.5 ppm dose on THP1 cell line. The highest inhibition was achieved at 50 ppm dose as 85,8% for THP1 cell line and 73.3% for A549 cell line. Based on this results, we concluded that temu ireng ethanol extract has a poliferation inhibition activity on both cell lines and has a potential substance to be develop as antitumor.
Keyword: A549, curcuma aeruginosa Roxb, inhibition activity, THP1

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