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: Pengembangan Sistem Cara Produksi Makanan Enteral yang Baik (CPMEB) dan Aplikasinya di RSPAD Gatot Soebroto Ditkesad Jakarta
Abstrak: Hospital formula enteral food is a ready to eat (RTE) food categorized as a special food because it is targeted specifically for group of people with health risk. Therefore, the safety of this enteral food needs to be controlled more stringenly than other RTE food. One of the basic food safety management that can be applied is GMP (Good Manufacturing Practices). Presently guidelines for good processing method for enteral food is not available yet. This research was aimed to develop a GMP system for enteral food or CPMEB (Cara Produksi Makanan Enteral yang Baik) consisting a guideline as well as the auditing system, and its application in Gatot Soebroto Hospital Jakarta. The system was development based on the Indonesian Health Ministry Regulation Number: 1096/MenKes/PER/VI/2011 on hygiene and food services sanitation; The National Agency of Drug and Food Control Regulation2011 Number: HK.03.1.23.12.11.10720 on the guidelines for the production of processed food products for baby powder formula and advanced powder formula; The National Agency of Drug and Food Control Decree2003 Number: HK. 00.05.5.1639 on the guidelines for food production for home industry; and other relevant references. Based on the literature review and trials, the CPMEB guideline and its audit system applicable to the enteral production unit of the hospital were developed. Thirteen aspects were defined for the requirements; including four main aspects. The main aspects were criteria with higher priority. The aspects belong to this group were the production room, production equipment, process control and workers' hygiene. The rest of the aspects include building and its facilities, sanitation facility, raw materials storage, monitoring management, pest control, enteral food distribution, training, and patient feeding. The trial at Gatot Soebroto hospital shows that the enteral food production unit can be categorized as good; with improvements needed for several aspects such as: production equipment storage, hygiene and sanitation maintenance, blender handling sanitation procedure, process control for type of container, volume of container, production notes, enteral food storage, food distribution and training.
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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