Judul: Pembuatan Minuman Ringan Berkarbonat dari Teh
Abstrak: Teh merupakan minuman penyegar karena dengan meminumnya baik pada saat udara panas maupun dingin, orang akan merasa lebih segar. Selain memberikan kesegaran, teh juga telah ditemukan mencegah beberapa jenis penyakit.
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Judul: Pembuatan minuman berkarbon sari lidah buaya (Aloe vera)
Abstrak: Minuman berkarbon sari lidah buaya dibuat dari daun lidah buaya (Aloe vera) yang dihancurkan dan diekstrak sarinya. Sebelum diolah, daun lidah buaya disimpan dalam lemari es untuk mengurangi bau langunya. Penambahan asam sitrat 0.12 persen dan garam dapur 0.025 persen ditujukan untuk mengurangi jumlah saponin dan rasa getir. Sedangkan penjernihan pekatan dilakukan dengan penambahan bentonite sebanyak 0.2 persen. Jumlah pekatan yang digunakan pada minuman akan ber- pengaruh terhadap pH, kadar CO2, keasaman, total gula, kekentalan, total padatan terlarut, dan penilaian orga- noleptik. Total padatan terlarut, total gula, keasaman, kekentalan, dan pH akan naik dengan semakin banyaknya pekatan yang digunakan sedangkan kadar CO2 dan peni- , laian organoleptik akan menurun. Pasteurisasi setelah pembotolan dan penambahan na- trium benzoat berpengaruh langsung terhadap pertumbuhan kapang dan khamir yang selanjutnya akan mempengaruhi konsistensi minuman. Selama penyimpanan, keasaman dan total kapang/khamir meningkat, sedangkan kekentalan dan kadar 002 akan menurun. Total gula dan total padatan terlarut meningkat pada awal penyimpanan dan menurun pada periode penyimpanan selanjutnya….
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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