Judul: Kajian Kesadaran dan Perilaku Ibu Rumah Tangga Terhadap Keamanan Pangan di Kota dan Kabupaten Bogor
Abstrak: Housewife played an important role as household food safety gate keeper therefore study of food safety risk awareness as well as food safety behaviors and opinion to food regulatory system is needed as a basis for developing policies and interventions. Research method used was survey questionnaire method which used purposive sampling method. A total of 139 questionnaires were distributed to housewifes in Bogor. Genetically modified food, foodborne disease, and food iradiation were not considered yet but respondent gave enough attention to food safety risk. Vegetable vendors became first priority place for shopping and the price became the main aspects to be considered both for fresh and processed food. The most influential information source was television. Majority of respondents felt confident (57%) and satisfied (52%) with the performance of The National Agency af Drug and Food Control (NA-DFC). Respondents made food-handling errors especially on determining doneness of meat and preventing cross-contamination however food handling behavior towards application five keys of food safety was good with an average value of 3.99 out of 5 and a standard deviation of 0.37. Education levels and expenditure positively correlated with the behavior of respondents in implementing the five keys of food safety therefore food safety socialization to the low educated and midle-low income housewife is needed.
Keyword: survey, housewife, food safety, behavior, awareness

Judul: Hubungan antara pengetahuan gizi dengan persepsi mengenai keamanan pangan jajanan pada guru SD di Bogor
Abstrak: The general objective of this study was to investige nutritional knowledge and perception about food safety of teacher elementry school in Bogor. The research was conducted using a cross sectional study. The number of samples for each region was 23, sample was selected purposively. The percentage of nutritional knowledge level was 65.2% in rural area and 87% in urban area. The percentage of food safety knowledge level was 69.6% in rural area and 69.6% in urban area. The percentage of perception about food safety level was 78.3% in rural area and 95.7% in urban area. The result of independent sample t-test toward characteristic sample, nutritional knowledge, food safety knowledge, and perception about food safety indicate there was no difference (p>0.05) beetwen rural area and urban area, but there was a few characteristic sample which indicate there was a real difference (p<0.05) beetwen rural area and urban area.The result of correlation spearman test indicate there was no significant correlation (p>0.05) beetween characteristic samples with nutritional knowledge, except one characteristic sample that was training/meeting about nutrition indicate there was significant correlation with nutritional knowledge (p<0.05). The result of correlation spearman test indicate there was no significan correlation (p>0.05) beetwen characteristic sample with food safety knowledge. The result of correlation spearman test indicate there was no significant correlation (p>0.05) beetwen nutritional knowledge with food safety knowledge, nutritional knowledge with perception about food safety, and food safety knowledge with perception about food safety.
Keyword: 

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