Judul: Keragaan Status Gizi Anak Balita di Kecamatan Bogor Timur, Kota Bogor
Abstrak: Secara umum penelitian ini bertujuan untuk mengetahui keragaan status gizi anak balita dan faktor-faktor yang mempengaruhinya di Kecamatan Bogor Timur. Secara khusus penelitian ini bertujuan untuk mengidentifikasi karakteristik keluarga, mengetahui karakteristik ibu (akses terhadap informasi dan pengetahuan gizi ibu), mempelajari pola pengasuhan balita, mengetahui keragaan pola konsumsi pangan anak balita, menganalisis keragaan status gizi anak balita, dan menganalisis faktor-faktor yang berhubungan dengan status gizi balita. Hasil dari penelitian ini diharapkan dapat memberikan informasi mengenai keadaan status gizi anak balita. Selain itu bagi masyarakat khususnya ibu-ibu, Puskesmas maupun Posyandu, penelitian ini diharapkan dapat memotivasi adanya upaya-upaya kegiatan atau program untuk meningkatan status gizi anak balita.
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Judul: Hubungan Beban Kerja, Pengetahuan dan Sikap Gizi Ibu, serta Pola Asuh Makan dengan Status Gizi Balita di Kota Bogor.
Abstrak: Penelitian ini bertujuan untuk menganalisis hubungan beban kerja, pengetahuan dan sikap gizi ibu, serta pola asuh makan dengan status gizi balita. Desain penelitian ini adalah cross sectional dengan lokasi penelitian di Kelurahan Paledang, Kota Bogor yang ditentukan secara purposive. Subjek dalam penelitian ini adalah 80 balita usia 3—5 tahun dengan teknik penarikan contoh proportional random sampling. Hasil penelitian menunjukkan bahwa sebagian besar keluarga memiliki pendidikan dan pendapatan yang rendah. Umur balita dan pola asuh makan memiliki hubungan positif signifikan dengan status gizi balita, namun beban kerja, pengetahuan dan sikap gizi ibu tidak memiliki hubungan signifikan dengan status gizi balita (p>0.05). Hubungan yang signifikan terdapat pula antara beban kerja dengan kuantitas pengasuhan dan sikap gizi dengan pola asuh makan (p<0.05). Faktor yang berpengaruh terhadap status gizi adalah umur balita dan pola asuh makan.
Keyword: balita, beban kerja, pola asuh makan, status gizi

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