Judul: Pengaruh Iradiasi terhadap kandungan B-Karoten dan daya simpan wortel
Abstrak: Sayuran merupakan bahan pangan sumber vitamin dan mineral yang sering mengalami kerusakan pasca panen, sehingga diperlukan teknologi pengawetan yang baik. Teknik iradiasi merupakan salah satu cara pemanfaatan teknologi canggih untuk pengawetan bahan pangan. Tujuan penelitian ini adalah untuk mengetahui pengaruh iradiasi terhadap kandungan B-karoten dan daya simpan wortel. Perlakuan yang diberikan terhadap wortel yaitu perlakuan 1 dosis iradiasi yang terdiri dari dosis 0 kGy, kGy, 2 kGy, 3 kGy dan lama penyimpanan yaitu 0 minggu, 1 minggu, 2 minggu, 3 minggu dan 4 minggu. Penyimpanan dilakukan pada suhu 8 °C dan dikemas dalam plastik polietilen berlubang.
Keyword: iradiasi

Judul: Pengaruh iradiasi terhadap kandungan gizi daya awet daging ayam
Abstrak: Tujuan penelitian ini adalah untuk mengetahui penga- ruh iradiasi dan lama penyimpanan terhadap kandungan gizi serta pengaruh iradiasi terhadap daya awet daging ayam. Penelitian ini dilakukan dalam dua tahap yaitu penelitian pendahuluan dan penelitian lanjutan. Penelitian pendahu- luan dimaksudkan untuk menentukan taraf perlakuan dosis iradiasi dan suhu iradiasi dengan efek samping yang mini- mum. Selain itu, juga dimaksudkan untuk menentukan se- lang waktu usia simpan untuk pengamatan. Berdasarkan ha- sil penelitian pendahuluan, maka proses iradiasi dalam penelitian lanjutan dilakukan pada suhu beku (-20 °C) de- ngan dosis iradiasi O (tanpa iradiasi), 1, 2 dan 3 kGy (kilogray) serta lama penyimpanan masing-masing 0, 3, 6, 9, 12 dan 15 hari dengan suhu simpan 5 - 10 °C. Pengamatan dilakukan terhadap sifat kimia dan fisik daging ayam yang meliputi kandungan protein, air dan le- mak serta pengukuran pH dan keempukan. Daya awet daging ayam ditentukan melalui pengujian organoleptik terhadap aroma, warna, lendir dan kekenyalan daging ayam. Data pengamatan sifat kimia dan fisik, diuji dengan "sidik ragam" sedangkan data pengamatan ungan "Friedman Test". ...
Keyword: 

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