Judul: Uji toksisitas bubuk ekstrak kompleks Cu-turunan klorofil (Na-Cu-Klorofin) daun cincau hijau (Premna oblongifolia Merr.) sebagai bahan baku suplemen makanan
Abstrak: Suplemen makanan berbasis klorofil banyak beredar di Indonesia, yang diyakini dapat membantu meningktkan kesehatan, dimana hampir semua merupakan impor dan berharga mahal. Sebagai negara tropis, Indonesia memiliki ketersediaan sumber-sumber klorofil dari tanaman sangat besar. Oleh karena itu, eksplorasi terhadap sumber-sumber klorofil perlu dikembangkan untuk dijadikan bahan baku suplemen makanan. Manfaat klorofil dan turunannya bagi kesehatan antara lain: antioksidan antimutagenik, menurunkan serum kolesterol dan trigliserida, meringanlan konstipasi kronis.
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Judul: Karakteristik fisiko-kimia dan uji toksisitas bubuk Cu-turunan klorofil (Cu-Chlorophyllin) daun murbei (Morus alba L.) sebagai prototipe bahan suplemen makanan
Abstrak: Klorofil dan beberapa turunannya memiliki manfaat untuk meningkatkan kesehatan, sehingga bisa dimanfaatkan sebagai suplemen makanan (Hendler & Rorvik 2001; Prangdimurti 2007; Limantara 2009). Klorofil memiliki sifat labil dan mudah berubah menjadi bentuk turunannya jika terkena cahaya, panas, oksigen dan degradasi kimia (Gross 1991). Oleh sebab itu perlu dilakukan proses penambahan Cu sehingga membentuk Cu-turunan klorofil yang lebih stabil (Hendry & Houghton 1996). Sumber klorofil yang digunakan adalah daun murbei (Morus alba L.) varietas Kanva dengan kandungan klorofil sebanyak 844 ppm (Kusharto et al 2008). Budidaya tanaman murbei di Indonesia telah lama dilakukan, khususnya untuk pakan ulat sutera. Namun peternakan ulat sutera umumnya baru menghasilkan produk berupa kokon sebagai bahan baku produksi benang sutera yang harga jualnya relatif rendah. Penelitian ini secara umum bertujuan untuk menganalisis karakteristik fisiko-kimia dan uji toksisitas bubuk Cu-turunan klorofil (Cu-Chlorophyllin) daun murbei (Morus alba L.) sebagai prototipe bahan suplemen makanan.
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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