Judul: Fortifikasi Zat Besi pada Mie Kering yang Dibuat dari Campuran Tepung Terigu dan Tepung Singkong
Abstrak: Dalam penelitian ini dipelajari cara pembuatan tepung singkong dengan kadar HCN serendah munqkin. Selain itu juga dipelajari peningkatan nilai tambah tepung singkong sebagai pensubstitusi tepung terigu dalam pembuatan mie, serta fortifikasi zat besi ke dalam mie tersebut. Penelitian ini terbagi dalam tiga tahap. Tahap pertama adalah tahap pemilihan proses pembuatan tepung singkong yang baik. Tahap kedua merupakan tahap formulasi dan pembuatan mie. Dan pada tahap ketiga diamati pengaruh penyimpanan terhadap mutu mie yang dipilih dari tahap kedua, yang dilakukan setiap dua minggu selams delapan minggu (dua bulan).
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Judul: Mempelajari fortifikasi zat besi pada bumbu mie rasa opor dan semur serta kestabilannya selama penyimpanan
Abstrak: Tujuan dari penelitian ini adalah untuk mengetahui kadar zat besi, kandungan anti nutrisi yang dapat mempe- ngaruhi bioavailabilitas zat besi pada rempah-rempah yang telah diformulasi menjadi bumbu opor dan semur, mempelajari kemungkinan fortifikasi zat besi pada bumbu rempah tersebut dan kestabilannya selama penyimpanan. Penelitian ini terbagi dalam tiga tahap. Penelitian tahap I adalah tahap pembuatan dan formulasi bumbu mie instan rasa opor dan semur serta analisis terhadap kadar air, kadar total besi, ketersediaan zat besi secara in vitro dan kandungan senyawa antinutrisi (asam fitat, tanin dan asam oksalat) pada bumbu tersebut. Penelitian tahap II adalah tahap pemilihan konsentrasi zat besi baik fero sulfat maupun fero fumarat yang difortifikasikan pada bumbu opor dan semur berdasarkan uji organoleptik. Sedangkan pada penelitian tahap III adalah tahap penyimpanan bumbu yang telah difortifikasi dengan fero sulfat dan fero fumarat dengan konsentrasi zat besi terpilih pada penelitian tahap II. Pengamatan dilakukan setiap dua minggu terhadap kadar total zat besi, ketersediaan zat besi secara in vitro dan kadar air. ...
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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