Judul: Pengaruh Program Pemberian Tablet Tambah Darah (TTD) Terhadap Perbaikan Status Besi pada Remaja Putri di Kota Bogor
Abstrak: Anemia merupakan masalah gizi mikro yang banyak terjadi di seluruh dunia terutama di negara berkembang yang diperkirakan terjadi pada 30% populasi penduduk dunia. Sebesar 29% Wanita Usia Subur (WUS) yang tidak hamil mengalami anemia serta 38% wanita hamil usia 15-49 tahun mengalami anemia (WHO 2011). Anemia pada remaja putri sampai saat ini masih cukup tinggi. Data Kemenkes (2013) menunjukkan prevalensi anemia gizi pada kelompok usia remaja (≥15 tahun) adalah 22.2%, meningkat dari data Kemenkes tahun 2007 yakni 19.7% terkait kejadian anemia pada usia remaja (Kemenkes RI 2007; Kemenkes RI 2013). ...
Keyword: anemia, efektivitas, remaja putri, suplementasi besi

Judul: Pola Konsumsi Pangan Sumber Zat Besi Pada Remaja Putri Peserta Program Pemberian Tablet Tambah Darah Di Kota Bogor.
Abstrak: Tujuan penelitian ini adalah mengkaji pola konsumsi pangan sumber zat besi dan bioavailabilitas zat besi pada remaja putri peserta pemberian tablet tambah darah di Kota Bogor. Desain penelitian yang digunakan adalah cross sectional study dengan subjek penelitian berjumlah 3798 orang yang berada di 19 SMP dan 20 SMA. Pangan sumber zat besi yang sering sering dikonsumsi adalah daging ayam dan telur ayam. Asupan zat besi 7.5 mg dengan tingkat kecukupan gizi 30.3%. Bioavailabilitas zat besi subjek tergolong rendah. Tidak terdapat hubungan antara pekerjaan orangtua, tingkat pendidikan orangtua, besar pendapatan orangtua dan jumlah uang saku dengan tingkat kecukupan zat besi (p>0.05).
Keyword: anemia, bioavailabilitas zat besi, konsumsi pangan, tablet tambah parah

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