Judul: Hubungan antara Bioavailabilitas Intake Zat Besi dengan Status Anemia Remaja di Yogyakarta dan Padang.
Abstrak: Masalah gizi mikro merupakan masalah gizi yang masih dihadapi oleh negara-negara berkembang seperti Indonesia. Defisiensi besi merupakan salah satu contoh masalah gizi mikro dan dapat menyebabkan terjadinya anemia. Defisiensi zat besi disebabkan oleh kurangnya intake zat besi atau intake zat besi sudah cukup namun dengan bioavailabilitas yang rendah. Tujuan dari penelitian ini adalah menganalisis hubungan antara bioavailabilitas intake zat besi dengan stasus anemia remaja di Kota Padang dan Yogyakarta. Penelitian ini menggunakan desain cross sectional study dan menggunakan sebagian data dari penelitian Dwiriani et al. (2013). Contoh dalam penelitian ini adalah siswa SMA di Padang (101 orang) dan Yogyakarta (98 orang) yang diperoleh secara purposive. Rata-rata asupan dan tingkat kecukupan energi dan zat gizi contoh di Yogyakarta signifikan lebih tinggi daripada contoh di Padang kecuali kalsium. Rata-rata kadar Hb contoh di Yogyakarta dan Padang relatif sama, namun contoh yang mengalami anemia di Yogyakarta (23.5%) relatif lebih tinggi daripada di Padang (12.9%). Terdapat hubungan signifikan yang positif (p<0.05) antara bioavailabilitas zat besi dengan status anemia remaja.
Keyword: bioavailabilitas, asupan zat besi, status anemia, remaja

Judul: Bioavailabilitas Besi Konsumsi Pangan pada Remaja Putri Anemia dan Non Anemia
Abstrak: The objective of this research was to assess bioavailability of iron intake among anemic and non anemic adolescent girls. The subjects were 80 high school student of SMAN 1 Cibungbulang Bogor. The dietary assessment was applied among 30 anemic and 50 non anemic student. The heme iron source student are 5.9 ± 7.7 mg and from non heme iron source are 8.6 ± 9.5 mg. Iron bioavailability are 1.4 ± 0.8 mg on anemic student and 1.2 ± 0.9 mg on non anemic student. The result of Pearson test showed that there is no significant corelation (p>0,05) between iron absorbed with adolescent anemic status.
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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