Judul: Metil-p-Hidroksibenzoat dari Fraksi Nonpolar Ekstrak Metanol Daun Ketepeng (Cassia alata)
Abstrak: Ketepeng (Cassia alata) adalah tanaman perdu yang tumbuh berkelompok dan berguna bagi kesehatan. Daunnya secara tradisional digunakan untuk mengobati sembelit dan penyakit kulit di banyak negara seperti Indonesia. Penelitian secara khusus pada daun ketepeng belum banyak dilakukan di Indonesia, terutama mengenai informasi komponen kimia dalam daun tersebut. Dalam penelitian ini, metabolit sekunder daun ketepeng dari Tangerang, Provinsi Banten diisolasi menggunakan metode ekstraksi dan berbagai teknik kromatografi, seperti kromatografi cair vakum, kromatografi radial, dan kromatografi lapis tipis preparatif. Uji fitokimia ekstrak metanol menunjukkan kandungan senyawa steroid/triterpenoid, flavonoid, alkaloid, saponin, dan tanin. Sebanyak 4 subfraksi dari fraksi nonpolar ekstrak metanol dianalisis menggunakan spektrofotometer resonans magnet inti. Hasil analisis menunjukkan bahwa salah satu subfraksi dari fraksi n-heksana-etil asetat (8:2) merupakan senyawa metil p-hidroksibenzoat, sedangkan struktur molekul dari 3 subfraksi lainnya belum dapat ditentukan karena masih berupa campuran.
Keyword: Cassia alata, ketepeng, kromatografi, metil p-hidroksibenzoat

Judul: Dugaan 4’-Hidroksi-6-C-xilofuranosil Flavanon dari Fraksi Polar Ekstrak Metanol Daun Ketepeng (Cassia alata)
Abstrak: Cassia alata, known as ketepeng in Indonesia, is an herb that has been traditionally used as ointment. The purpose of this study is to isolate and to identify compounds from polar fraction of the methanol extract from the leaves. Crude methanol extract of ketepeng leaves was fractionated briefly by liquid -vacuum chromatography. The eluates having the same separation pattern on thin-layer chromatography were combined and the fractions were grouped based on their polarity. H fraction eluted with methanol as eluent was fractionated further by gravitational column chromatography resulting 21 fractions. H9 fraction which showed single TLC spot with 3 different eluent mixtures, was further partitioned and then analyzed by using proton nuclear magnetic resonance (1H NMR) spectrophotometer and liquid chromatograph-mass spectrometer (LC-MS). The LC-MS chromatogram indicated a mixture of 4 compounds. Based on 1H NMR and LC-MS spectrum, the most abundant fraction in the chromatogram was predicted as a flavonoid C-glycoside compound, that is 4’-hydroxy-6-C-xylofuranosyl flavanone.
Keyword: ketepeng, flavonoid, flavanone, Cassia alata

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