Judul: Pola Pemecahan Karbohidrat Selama Fermentasi Tape Ubi Kayu Dengan Menggunakan Inokulum Murni Kering
Abstrak: Penelitian bertujuan untuk mempelajari: (1) pengaruh jenis inokulum murni kering terhadap perubahan sifat-sifat organoleptik dan komponen kimia tape ubi kayu yang dihasilkan, (2) pola perubahan karbohidrat (pati) selama fermentasi tape ubi kayu.
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Judul: Mempelajari pembuatan tepung tape ubi kayu
Abstrak: Tape ubi kayu merupakan makanan tradisional yang su- dah dikenal oleh masyarakat Indonesia pada umumnya. Peneli- tian mengenai tepung tape ubi kayu sampai saat ini belum pernah dilakukan, Tepung tape mempunyai masa depan yang ba- ik untuk dikembangkan karena dalam bentuk tepung, tape akan mampu disimpan dalam waktu yang lebih lama dan mudah diolah menjadi makanan lainnya. Tepung tape tetap memperta- hankan flavor dan, aroma tape yang spesifik serta sifat ta- pe yang mudah dicerna. Cara pengolahan tepung tape ubi kayu adalah dengan 1 mengeringkan tape ubi kayu untuk kemudian digiling keben- tuk tepung dengan pengayakan. Dalam penelitian ini diguna- kan ubi kayu jenis putih dan ubi kayu jenis kuning, dengan cara fermentasi dalam keranjang bambu dan fermentasi dalam udara terbuka, serta lama fermentasi selama 24, 36, dan 48 jam. Pengeringan dilakukan dengan menggunakan alat penge- ring RINSALI 80 buatan FTDC-IPB pada suhu 70 - 75 derajat Celcius dan penggilingan dengan alat penggiling palu (ham- mer mill). ...
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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