Judul: Pengaruh pemberian pangan yang difortifikasi zat multi gizi mikro terhadap status gizi ibu hamil dan berat bayi lahir
Abstrak: Nutritional problems, on pregnant women in Indonesia cover not only macro nutrients but also micronutrients deficiencies like Fe and Vitamin A. Nutritional improvement strategy through supplementary fortified foods for pregnant women nedds to be carried out to improve nutritional status of mothers and infant birth.
Keyword: Multi Micronutrients, Anemia, Ferritin, Retinol, Infant birth weight, Weight gain pregnant mother, Pemberian makanan tambahan (PMT)

Judul: Pengaruh Pemberian Pangan Yang Difortifikasi Zat Multigizi Mikro Pada Ibu Hamil Dan Pengasuhan Terhadap Pertumbuhan Linier, Perkembangan Motorik Dan Status Anemia Bayi
Abstrak: Seperti diberbagai negara berkembang lainnya, masalah kekurangan gizi makro dan mikro pada ibu dan bayi juga terjadi di Indonesia. Strategi perbaikan gizi secara dini dapat dilakukan dengan pemberian pangan yang difortifikasi zat multi gizi mikro pada ibu hamil, sebagai salah satu alternatif perbaikan gizi bagi generasi yang selanjutnya. Tujuan penelitian ini adalah untuk menganalisis dampak pemberian pangan yang difortifikasi zat multi gizi mikro pada ibu hamil dan pengasuhan terhadap pertumbuhan, perkembangan motorik dan status anemia bayi. Penelitian ini dilakukan pada 3 Kecamatan di Kabupaten Bogor yaitu di Ciampea, Leuwiliang dan Leuwisadeng. Penelitian ini dilakukan kohort prospektif dengan jumlah bayi yang diikuti 120 orang yang dibagi menjadi 3 kelompok. Kelompok pertama (kelompok fortifikasi) yang ibunya pada waktu hamil menerima pangan yang difortifikasi vitamin A, C, asam folat, besi, seng dan iodium. Kelompok kedua (tanpa fortifikasi) diberikan pangan yang sama tetapi tidak difortifikasi dan kelompok ketiga merupakan kelompok kontrol yang ibunya waktu hamil tidak menerima pangan fortifikasi maupun tanpa fortifikasi. Data yang dikumpulkan meliputi: status sosial ekonomi keluarga, pemberian ASI, pengasuhan, intik gizi ibu menyusui, berat badan ibu, intik gizi bayi, morbiditas, berat badan, tinggi badan, panjang lutut setiap bulan, perkembangan motorik, Ht dan Hb. Analisis zskor PB/U dan BB/U menggunakan referensi NCHS-WHO (1983) dan WHO (2006). Data ditabulasi, dianalisis secara statistik dengan Anova, Ancova, korelasi Pearson, regresi linier, regresi berganda dan regresi logistik berganda menggunakan program Software SPSS versi 10.0 dan 13.0.
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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