Judul: Enkapsulasi Metformin dengan Kitosan Nano Partikel sebagai Obat Antidiabetes Tipe II
Abstrak: Metformin sebagai obat antidiabetes tipe II merupakan obat yang terbukti ampuh. Metformin memiliki bioavailabilitas 50-60% dengan waktu paruh yang yaitu 1,5-3 jam. Oleh karena itu, diperlukan modifikasi metformin agar dapat mengurangi efek sampingnya. Tujuan penelitian ini adalah mengkarakterisasi nanopartikel kitosan berupa morfologi, ukuran partikel, gugus fungsi, dan membandingkan waktu paruh kitosan-metformin dengan metformin terhadap tikus galur Sparague dawley. Proses enkapsulasi antara kitosan dan metformin berhasil dilakukan. Hal ini dapat ditunjukkan ukuran kitosan membesar setelah proses enkapsulasi dengan meformin, peningkatan ukurannya sebesar 92,24 nm. Selain itu, hasil uji FTIR yang menunjukkan adanya penggabungan gugus fungsi kitosan dengan metformin dan terlihat pada foto SEM yang dihasilkan. Hasil uji in vivo menunjukkan bahwa kitosan-metformin dapat 4% lebih efektif menurunkan gula darah dibandingkan metfromin. Selain itu, dapat menurunkan gula darah hingga 4 jam.
Keyword: diabetes tipe II, metformin, nanokitosan, nanoenkapsulasi, nanokitosan-metformin

Judul: Enkapsulasi Nanokitosan pada Ekstrak Daun Tapak Dara (Catharanthus roseus) sebagai Antihiperglikemia
Abstrak: Diabetes Mellitus merupakan suatu kelainan metabolik kronis yang ditandai dengan kondisi dimana konsentrasi glukosa dalam darah lebih tinggi dari normal (hiperglikemia). Optimalisasi pengobatan herbal dapat dilakukan dengan proses enkapsulasi menggunakan nanokitosan. Tujuan dari penelitian ini adalah untuk menentukan dosis terbaik ekstrak daun tapak dara (Catharanthus roseus) terenkapsulasi nanokitosan pada tikus hiperglikemia sesaat. Penelitian ini dilakukan beberapa tahap, yaitu ekstraksi daun tapak dara, enkapsulasi nanokitosan, uji fitokimia, analisis PSA, SEM, dan FTIR, serta uji toksisitas dengan metode BSLT. Uji fitokimia menunjukkan esktrak daun tapak dara mengandung flavonoid dan saponin. Ukuran partikel ekstrak, nanokitosan dan ekstrak-nanokitosan berturut-turut yaitu 278,54; 273,36; 381,98 nm. Hasil analisis SEM dan FTIR menunjukkan terjadinya penggabungan antara ekstrak dengan nanokitosan. Perlakuan terbaik pada aktivitas antihiperglikemia yaitu dengan dosis pemberian ekstrak-nanokitosan 20 mg/g BB yang menurunkan kadar glukosa darah sebesar 68,9 mg/dL dari 140 mg/dL (tikus hiperglikemia) hingga jam ke-3.
Keyword: antihiperglikemia, enkapsulasi, fitokimia, tapak dara, ukuran partikel

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