Judul: Pengetahuan dan Sikap Gizi, Perilaku Makan serta Status Gizi Manula pada Panti Werdha di Kota Bandung.
Abstrak: Healthy aging yaitu menjadi tua tetapi tetap sehat merupakan tujuan utama setiap manusia (Darmojo, 2003). Bertambahnya usia mengakibatkan terjadinya penurunan fungsi organ tubuh yang dapat menyebabkan terjadinya gizi salah pada manula (Wirakusumah, 2000).
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Judul: Keterkaitan Konsumsi Pangan, Status Gizi dan Status Kesehatan Lansia di Kota Bandung
Abstrak: Decreases of physiological function in the body will occur in the elderly population. As a result, the elderly body’s ability to work normally is decreased, especially in term of consuming foods. The lack of food consumption in the elderly will affect their nutritional status and increase the risks of the occurrence of anemia and health status problems. The objective of this study was to know the relationships of food consumption, nutritional status, and health status of the elderly living in nursing homes and families at the City of Bandung. A retrospective study of 115 elderly people was conducted and data collected on May 2012. The study showed that level of energy intake was normal, protein was lack, calcium was lack, iron was adequate, and vitamins were lack. Correlation test showed that there was no correlation among level of energy, protein, calcium, iron, vitamin B1, B2, B6 and vitamin C intake to health status (p>0.05). However, there was correlation among level of protein intake to nutritional status, level of vitamin B1 and B2 intake to health status, nutritional status and anemia to health status, as well as blood pressure to anemia (p<0.05).
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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