Judul: Validasi sekunder metode analisa campylobacter jejuni pada daging ayam
Abstrak: Foodborne disease (penyakit akibat pangan) merupakan suatu penyakit yang diderita oleh seseorang akibat mengonsumsi makanan yang telah terkontaminasi bahan kimia beracun atau mikroba patogen. Salah satu gejala foodborne disease akibat kontaminasi mikroba patogen yaitu diare. Salmonella spp, Shigella spp dan Campylobacter spp merupakan bakteri-bakteri patogen penyebab diare yang banyak diderita oleh masyarakat. Mikroorganisme tersebut paling banyak ditemukan pada bahan pangan mentah berupa daging unggas, telur, susu, ikan dan sayuran. Campylobacter jejuni merupakan salah satu bakteri patogen yang sering mengontaminasi bahan pangan. Bakteri ini dapat mengontaminasi bahan pangan melalui kotoran ternak, selama proses pemerahan atau infeksi pada puting susu, unggas yang terinfeksi dan air yang tercemar (Stern dan Line 2000). Kasus penyakit diare akibat terinfeksi bakteri Campylobacter dibeberapa negara telah banyak dilaporkan, misalnya di Amerika Serikat dilaporkan sekitar 2,5 juta penderita campylobacteriosis dan 124 penderita meninggal dunia setiap tahunnya (Hu dan Kopecko 2003). Pada tahun 1998 kasus infeksi Campylobacter juga dilaporkan di Belanda sebanyak 3.398 kasus, di Denmark sebanyak 3.372 kasus, di Spanyol sebanyak 4.382 kasus (Schmidt et al. 2001). The Swedish Institute for Infection Desease Control (2008) melaporkan bahwa pada tahun 2007 total 7.106 kasus campylobacteriosis terjadi di Swedia, dengan 77,45 kasus setiap 100.000 populasi. Sedangkan di Indonesia, dari 21.763 penderita diare sekitar 3,6% nya disebabkan karena Campylobacter jejuni (Tjaniadi et al. 2003).
Keyword: Campylobacter jejuni, Foodborne disease, penyakit akibat pangan, mikroba patogen, Salmonella spp, Shigella spp, kontaminasi bahan pangan

Judul: Prevalensi campylobacter jejuni pada karkas ayam dan pengembangan uji deteksinya
Abstrak: Chicken meat and eggs are the main source of animal protein in Indonesia because they are relative cheaper than cattle products. Campylobacter jejuni is a foodborne zoonotic pathogen predominantly found in chicken carcasses. C. jejuni causes gastroenteritis in humans, had a very low infectious dose that is easy to cause infection in humans. The study was aimed to (1) rapidly detect C. jejuni contamination in chicken carcass (2) determine the prevalence of contamination and quantitative analyse of the risk of thermophilic Campylobacter sp. when mishandling consume. (3) produce immune sera against the local isolates that can be used as a reagent for ELISA. A total of 298 chicken carcass samples sold in modern and traditional markets in the area of Jakarta, West Java (Bogor and Sukabumi) and Central Java (Kudus and Demak) were collected and attempted for isolation following ISO/ DIS 10272-1994 protocol, identification using biochemical API Campy, and polymerase chain reaction (PCR) assay using hipO, glyA, fla, and 23S rRNA primer sets for species identification. The result is chicken carcasses sold in the sampling area both traditional markets and supermarkets are contaminated with C. jejuni and C. coli. Prevalence of Campylobacter sp. contamination on chicken carcasses was isolated by conventional (19.8%) and PCR (41.6%). The contamination rate of Campylobacter sp. on chicken carcasses sold in supermarkets, markedly 14.09% is higher than in traditional markets 5.70%. It is also confirmed that the prevalence for contamination of C. jejuni was higher than C. coli. Prevalence of C. jejuni contamination that sold in traditional markets 88.23% was higher than C. coli 11.76%. The prevalence of C. jejuni contamination in carcasses sold in swalayan was 78.57%. These were higher than contamination of C. coli that was identified by conventional methods 21.42%. Flagella and whole cell antigen purification from a local isolate of C. jejuni (C1) was done by glycine extraction and produced flagellar protein of 31 kDa. Animal immunization against flagellar protein extract induced higher specific antibody titers in chicken than rabbits and sheep. A probability model describing variability but not uncertainty was developed in beta-poisson model. The result is microorganism reduction 2 log cfu/gram and the output sof the model was the probability of illness per handling if the roasted chicken mishandled is 4 for 1 000 humans.
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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