Judul: Pengendalian Mutu dalam Proses Pembuatan Makanan Enteral di Rumah Sakit Dustira, Kota Cimahi, Jawa Barat
Abstrak: The goal of this research is to analyze the quality control process for each enteral feeding production step in Dustira Hospital. The design used in this research was cross sectional. This research was taken place from October until November 2011 in Dustira Hospital. The observation method use refered to Permenkes No.1096/Menkes/PER/V1/2011. The results showed that 90% food handler have good hygienic sanitation knowledge, but generally lacking in proper behavior. The result also showed that based on physical and sanitation facilities, the hospital is categorized as group B (total score 83.6%). Hygienic sanitation in the enteral nutrition production process does not meet the requirement (88.5%). Critical Control Point (CCP) was found in the processing step along with the risk which have to be controlled, that are physical (hair), biological (Salmonella, Shigella and Echericia colii), and cross contamination (food handler and utensil).
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Judul: Evaluasi Efektivitas Sanitasi pada Area Pendinginan dan Pengemasan Pada Produksi Mi Instan di PT. X Ciawi –Bogor
Abstrak: The research objectives were to evaluate the sources of recontamination product on cooling and packaging areas, the effectiveness of sanitation programs and personnel hygiene implemented in the cooling and packaging areas. The study was conducted at PT. X Ciawi, Bogor, from August through October 2011. The results of application of the basic requirements or CPMB indicated 5 deviations, ie, 4 minor nonconformances and 1 major nonconformance in the category rating of A (excellent). Employee understanding of hygiene and sanitation was good, showed by the questioners distributed to all employees. Microbiological recontamination sources of cooling area were found in the equipments such as conveyors, fans, and chains of cooling chamber unit. However the average number of TPC and mold were still under the internal standard (1.0 X 102 CFU/ml/cm2) established by the company. Contamination of yeast, E.coli and coliform were not found. On packaging area at the part of a tool such as conveyors, seasoning buckets and seal machine, the microbial contamination (TPC) was also found under the internal standard (1.0 X 102 CFU/ml/cm2). However other microbial contaminants such as mold, yeast, E.coli and coliform were negatives. Based on these findings, it can be concluded that the application of sanitation programs on the equipments of cooling and packaging areas were quite effective. Observation of air microbiological quality in the areas of cooling and packaging showed that contamination of TPC, molds and yeasts were under the internal standard (1.0 X 102 CFU/ml/cm2). Similar results were obtained from the cooling and packaging areas where the density of TPC, molds and yeasts were found, the values were under the internal standard (1.0 X 102 CFU / 15 minutes / 100cm2). The implementation of personnel hygine around cooling and packaging areas were effective shown by the data of equalize staphylococcus aureus and coliform were all negatives. The average amount of TPC contamination on the hands of employees were under the internal standard (1.0 CFU/ml/cm2 X 102), which indicated that personnel hygiene programs that had been implemented by the company were effective. In general it can be concluded that the implementation of GMP on particular areas of cooling and packaging at least as a basic requirements of the food industry had been met by PT. X
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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