Judul: Analisis Asupan Air pada Ibu Hamil di Indonesia berdasarkan Studi Diet Total
Abstrak: Air merupakan zat gizi esensial yang sangat penting bagi tubuh manusia termasuk ibu hamil. Tujuan penelitian ini adalah untuk menganalisis asupan air pada ibu hamil di Indonesia berdasarkan Studi Diet Total (SDT). Penelitian ini menggunakan data sekunder yang diperoleh dari data SDT 2014 dengan jumlah subjek 606 orang. Total asupan air terdiri dari air minuman, air dari makanan dan air metabolik. Air makanan dan minuman diperoleh dengan metode food recall 24 jam. Analisis asupan air berdasarkan Daftar Komposisi Bahan Makanan (DKBM) dan nutrition fact. Jenis minuman yang paling sering dikonsumsi subjek adalah air putih (100%), teh (30.2%) dan susu (26.1%). Ratarata asupan air total subjek adalah 2 027.3±698.8 mL/hari yang berasal dari air minuman (63.3%), air dari makanan (24.1%) dan air hasil metabolik (10.6%). Secara umum tingkat pemenuhan kebutuhan air subjek masih kurang yaitu 85.3%. Persentase asupan air subjek yang defisiensi berat dan defisiensi sedang yaitu 29% dan 25.6%. Pendidikan merupakan faktor yang mempengaruhi asupan air subjek.
Keyword: asupan air, ibu hamil, minuman.

Judul: Asupan Kalsium, Natrium dan Kalium pada Ibu Hamil di Indonesia Berdasarkan Studi Diet Total
Abstrak: Ibu hamil merupakan kelompok yang rentan terhadap kekurangan zat gizi mikro. Tujuan penelitian ini menganalisis asupan kalsium, natrium dan kalium pada ibu hamil di Indonesia. Penelitian ini menggunakan data sekunder hasil Studi Diet Total (SDT). Konsumsi pangan dikumpulkan menggunakan metode recall 24 jam. Analisis kalsium, natrium dan kalium berdasarkan tabel komposisi pangan United States Department of Agriculture (USDA), Tabel Komposisi Pangan Indonesia (TKPI), Nutri Survey dan Nutrition Fact. Jumlah subjek penelitian ini 606 ibu hamil. Rata-rata asupan kalsium, natrium dan kalium subjek sebesar 403.5±343.1, 1 562.3±707.8 dan 1481.2±795.0 mg/hari. Sebagian besar subjek memiliki tingkat pemenuhan kalsium dan kalium kategori kurang. Sebanyak 12.5% subjek memiliki tingkat pemenuhan natrium kategori lebih. Faktor risiko kekurangan kalsium pada subjek adalah pendidikan. Faktor risiko kekurangan kalium adalah pendidikan dan status pekerjaan, sedangkan faktor risiko kelebihan natrium adalah jumlah anggota rumah tangga.
Keyword: ibu hamil, kalium, kalsium, konsumsi pangan, natrium

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