Judul: Hubungan Pengetahuan Gizi, Konsumsi Pangan Goitrogenik dan Garam dengan Kadar Iodium Urin Ibu Hamil di Desa Gekbrong Cianjur
Abstrak: Penelitian ini bertujuan untuk menganalisis hubungan antara pengetahuan gizi, konsumsi pangan goitrogenik dan garam dengan kadar iodium urin ibu hamil di Desa Gekbrong, Cianjur. Desain penelitian adalah cross sectional study. Jumlah ibu hamil pada penelitian sebanyak 50 orang. Penelitian dilakukan di Desa Gekbrong pada bulan Februari-Mei 2016. Hasil uji hubungan menunjukkan terdapat hubungan negatif secara signifikan antara hubungan konsumsi pangan goitrogenik baik berdasarkan frekuensi maupun kandungan tiosianat dengan kadar iodium urin dan hubungan antara pengetahuan gizi dengan frekuensi konsumsi pangan goitrogenik (P value <0.05). Namun, tidak terdapat hubungan secara signifikan antara hubungan pengetahuan gizi dengan konsumsi garam, hubungan antara pengetahuan gizi dengan kandungan tiosianat, hubungan antara usia dengan kadar iodium urin, hubungan antara pengetahuan gizi dengan kadar iodium urin dan hubungan antara konsumsi garam dengan kadar iodium urin (P value >0.05).
Keyword: garam, goitrogenik, iodium

Judul: Hubungan Pengetahuan, Sikap dan Praktik Gizi Ibu dengan Konsumsi Pangan Sumber Yodium dan Penggunaan Jenis Garam Rumah Tangga di Wilayah Pegunungan Kabupaten Cianjur
Abstrak: This study aimed to analyze relationship between mother nutrition knowledge, attitude, and practice and consumption of iodine source and consumption of salt among households in Cianjur highland area. This study was a cross-sectional study, conducted on 153 mother of 4th and 5th grades elementary school students. Iodine source food which frequently consumed were salted fish (68.8%) and eggs (66.7%). Spearman Rank correlation test showed that there ware significant correlations between nutrition knowledge and nutrition attitude (p=0.001; r=0.263), nutrition knowledge and nutrition practice (p=0.003; r=0.221), nutrition practice and food consumption (p=0.064; r=0.124), nutrition attitude and consumption of salt (p=0.064; r=-0.124), and nutrition practice and selection kinds of salt (p=0.004; r=0.216). No significant correlation between nutrition knowledge and consumption of salt (p=0.156); nutrition attitude and nutrition practice (p=0.103); nutrition knowledge and consumption iodine food (p=0.349); and nutrition attitude and consumption iodine food (p= 0.201).
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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