Judul: Kebiasaan Sarapan pada Remaja Siswi Sekolah Menengah Kejuruan di Bogor
Abstrak: The study was aimed to describe breakfast habit in teenage girls of vocational high school Bogor. Design of this study was a cross sectional and the subject was 68 students 14–18 years old. Breakfast consumption was collected by a 7- day food record and verified by researcher. The result showed that there are 45.6% teenage girls having breakfast regularly. Breakfast frequency per week is associated with BMI and anaemic status. The subject mostly answer breakfast was defined as eating in the morning. Half of the subject answer breakfast was defined as eating in the morning is beneficial and the other answered eating in the morning consist of a solid food and beverage with medium portion. Food and drink for breakfast was good by subject is bread and milk. The subject declare breakfast is important, but also the subject ever not breakfast because wake up late. Almost all of subject declared should be mother who prepare breakfast and must breakfast at home before starting activity. The teenage girls having a good quality breakfast with higher consumption of rice, bread, fruit, and milk than teenage girls having a low quality breakfast with higher consumption of sweet tea and snack was found in anaemic status (13.2%). Mother education, mother occupation, parents income, and number of family member were related to habitual breakfast (p<0.05). There is positive associated between habitual breakfast and quality breakfast (p=0.000 ; r=0.539).
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Judul: Kebiasaan Sarapan, Konsumsi Buah dan Sayur, dan Status Gizi Siswa Sekolah Menengah Pertama di Bogor
Abstrak: Fruits and vegetables are very important for consumption, especially for school-age children and adolescents. The purpose of this study were to analyze breakfast habits, fruits and vegetables consumption, and students’s nutritional status of junior high school in Bogor. The design of this study was cross-sectional with purposive sampling technique as much as 50 students in SMP Negeri 8 Bogor. Fruits and vegetables that consumed by students was included low as category. The result showed there was male students consumed breakfast more frequent than female students. Students’s nutritional status were categorized as normal. Correlation test showed there were no significant relationship (p>0.05) between individual and family characteristic, except households income with breakfast habits. There were no significant relationship (p>0.05) between individual and family characteristic, availability of fruits and vegetables at home, and parental habits of fruits and vegetables consumption, except households income with students of fruits consumption. Breakfast habits and fruits and vegetables consumption there were no significantly associated (p>0.05) with students’s nutritional status.
Keyword: Bogor Agricultural University (IPB), students, nutritional status, fruits and vegetables, breakfast habits

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