Judul: Hubungan Karakteristik Keluarga, Pengetahuan dan Sikap Gizi, serta Perilaku Hidup Bersih dan Sehat dengan Status Gizi Ibu Di daerah Kumuh, Jakarta Selatan.
Abstrak: Tujuan penelitian ini adalah menganalisis hubungan karakteristik keluarga, pengetahuan gizi, sikap gizi serta perilaku hidup bersih dan sehat(PHBS) terhadap status gizi ibu. Penelitian ini menggunakan data sekunder. Subjek dalam penelitian ini adalah ibu dengan kriteria tidak hamil. Hasil penelitian menunjukkan terdapat hubungan yang signifikan (p<0.05) antara pengetahuan gizi dengan sikap gizi. Terdapat hubungan signifikan (p<0.05) antara sikap ibu dengan tingkat kecukupan protein dan energi. Tidak terdapat hubungan signifikan (p > 0.05) antara perilaku hidup bersih dan sehat dengan tingkat kecukupan protein dan energi. Tidak terdapat hubungan antara Perilaku Hidup Bersih dan Sehat dengan status gizi ibu.Terdapat hubungan positif yang signifikan antara usia dengan status gizi ibu. Tidak terdapat hubungan positif antara variabel lain dengan status gizi. Terdapat dua kelompok berbeda berdasarkan hasil uji Klaster analisis, yaitu kelompok masyarakat sungai dan masyarakat rel kereta api.
Keyword: Daerah Kumuh, Pengetahuan gizi, PHBS, Sikap gizi, Status gizi.

Judul: Hubungan Antara Praktek Perilaku HIdup Bersih dan Sehat (PHBS), Pola Asuh Makan, dan Keluarga Sadar Gizi (Kadarzi) dengan Status Gizi Balita di Kecamatan Bantar Gebang
Abstrak: Tujuan dari penelitian ini adalah untuk menganalisis hubungan antara praktik Ibu tentang Perilaku Hidup Bersih dan Sehat (PHBS), praktik pemberian makan, dan Kesadaran Gizi Keluarga (Kadarzi) dengan status gizi balita anak-anak berusia tahun. Penelitian ini berlokasi di Kelurahan Ciketing Udik, Kecamatan Bantar Gebang Kota Bekasi. Desain cross sectional digunakan dalam hal ini belajar. Jumlah sampel dalam penelitian ini adalah 72 anak balita. Uji korelasi spearman menunjukkan tidak terdapat korelasi yang signifikan antara pengetahuan gizi ibu dengan kadarzinya dan praktik pemberian makan (p>0,05). Uji korelasi spearman juga menunjukkan ada yang tidak signifikan hubungan antara praktik Kadarzi yang dilakukan ibu dengan status gizi anak (z-score berat badan per umur (WAZ), z-score panjang badan per umur (LAZ), dan z-score berat badan per tinggi badan (WHZ)) (p>0,05). Selain itu hasilnya juga menunjukkan adanya hubungan yang signifikan antara praktik PHBS ibu dengan status gizi (z-score berat badan per umur (r=0,232; p=0,050) dan z-score panjang badan per umur (r=0.362; p=0.002)) dan praktik pemberian makan dengan status gizi (z-score panjang badan per umur (r=0.253; p=0.032)).
Keyword: Family nutritional awareness (Kadarzi), Clean and Healthy Behaviour (PHBS), Feeding practice, Nutritional status, Under five years old children

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