Judul: Pengetahuan Gizi, Keluhan Kesehatan, Kondisi Psikologis, dan Pola Pemberian Air Susu Ibu (ASI) Ibu Postpartum
Abstrak: Postpartum period is restoration period after childbirth with one of characteristics is the process of breastfeeding. This study was aimed to assess of nutritional knowledge, health complaints, psychological conditions, and their association with breastfeeding pattern on postpartum mother. A cross sectional study design and interview method was conducted in five rural areas in Dramaga Subdistrict, Bogor District, during the period of April to May 2013. Sample included in this study were 30 postpartum mothers who met inclusion criteria sample is the age of a baby 10−40 days and baby was not a first childbirth, she will be the respondent through the informed consent agreement, and be able communicate. The mayority postpartum mother had level of nutritional knowledge (60%) and health complaints (66.7%) were classified in low, and they have depression (56.7%). The nutritional knowledge of exclusive breastfeeding tends to correlate (r=0.126, p=0.508) exclusive breastfeeding practice. Meanwhile, lower health complaint tends to correlate with better breastfeeding practices.
Keyword: postpartum mother, breastfeeding, psychological, health complaints, Nutritional knowledge

Judul: Nutritional Status, Breastfeeding Knowledge, and Breastfeeding Practice in Cirebon Regency
Abstrak: Penelitian ini bertujuan untuk menganalisis hubungan status gizi ibu (asupan zat gizi dan indeks massa tubuh) dan pengetahuan ASI dengan praktik menyusui bayi usia 0–6 bulan di Kabupaten Cirebon. Desain penelitian ini adalah cross sectional study dengan jumlah subjek sebanyak 44 orang. Data yang digunakan merupakan data sekunder. Penelitian berlokasi di tiga desa di Kecamatan Gegesik, Kabupaten Cirebon yang merupakan lokus stunting. Sebanyak 47,7% subjek memiliki status gizi normal dan 29,5% subjek memiliki status gizi obesitas. Sebagian besar subjek memiliki tingkat kecukupan energi dan zat gizi yang belum mencapai kebutuhan harian. Sebanyak 63,6% subjek memiliki pengetahuan tentang ASI yang baik dan 43,2% subjek memiliki praktik menyusui yang kurang sesuai. Tidak terdapat hubungan signifikan antara tingkat kecukupan energi dan zat gizi ibu dengan status gizi bayi (p>0,05). Tidak terdapat hubungan signifikan antara karakteristik, status gizi, dan pengetahuan ibu mengenai pemberian ASI dengan praktik menyusui (p>0,05)., The purpose of this study is to analyze the relationship between maternal nutritional status (nutrient intake and body mass index) and breastfeeding knowledge with breastfeeding practices for infants aged 0-6 months in Cirebon Regency. The design of this research is a cross sectional study with a total of 44 subjects. The data used is secondary data. The study is located in three villages in Gegesik District, Cirebon Regency which were the locus of stunting. The amount of 47.7% subjects have normal nutritional status and 29.5% of subjects have obese nutritional status. Most of the subjects had adequate levels of energy and nutrients that had not yet reached their daily needs. The amount of 63.6% subjects have good knowledge of breastfeeding and 43.2% of the subjects have inappropriate breastfeeding. There is no significant relationship between the level of energy and nutritional adequacy of the mother and the nutritional status of the infants (p>0.05). There is no significant relationship between maternal characteristics, nutritional status, and knowledge of breastfeeding with breastfeeding practices (p>0.05).
Keyword: breastfeeding, breastfeeding knowledge, breastfeeding practice, nutritional adequacy, nutritional status

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