Judul: Kajian Mutu Mikrobiologi Produk Minuman Tradisional Hasil Olahan Industri dan Jamu Gendong
Abstrak: Beras kencur, sari asam, sari temulawak dan sari kunyit adalah beberapa dari sekian banyak minuman tradisional yang telah dikenal sejak lama oleh masyarakat Indonesia sebagai minuman jamu gendong dan akhir-akhir ini telah dikembangkan oleh industri-industri pangan sebagai produk minuman fungsional. Khasiat dari minuman tersebut telah lama diyakini oleb masyarakat Indonesia, akan tetapi seperti halnya produk tradisional lainnya maka perlu diperhatikan segi keamanannya. Tujuan dari penelitian ini adalah untuk mengidentifikasi dan mengkaji keamanan mikrobiologi keempat jenis produk minuman tradisional hasil olahan industri, baik yang diproduksi oleh industri kecil maupun industri besar. Uji mikrobiologis produk minuman tradisional tersebut akan diubungkan dengan jenis produk, bentuk produk, jenis kemasan, kode pendaftaran dari Departemen Kesehatan dan batas kadaluarsa, lalu dibandingkan dengan hasil uji mikrobiologi jamu gendong.
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Judul: Development and Implementation of Good Jamu Gendong Production Practice to Improve Its Microbiological Quality and Safety
Abstrak: Jamu gendong is a traditional Indonesian herbal beverage that can be considered as functional beverages because of their flavonoid content and essential oils from its herbs and spices. Although they are believed to help maintain good health, they are often considered low in quality and safety. This study aims to assess the microbiological quality of jamu gendong from two jamu gendong producers in Bogor using parameters such as microbiological quality of utensils, workers, processing and product to be used in developing a Good Jamu Gendong Production Practice (GJGPP) guideline for a home industry scale and implement it to those jamu gendong producers. This study consist of evaluation of production steps through observation, development of GJGPP guidelines by taking into considerations of Good Food Production Practice for home industry issued by The Indonesian National Agency for Drug and Food Control, implement the GJGPP guideline and evaluation of microbiological quality (Total Plate Count, Salmonella sp. and Staphylococcus sp. analysis) of the investigated products (beras kencur and temulawak extract), utensils (bottles) and environment (air sanitation) before and after implementation. The results obtained from this study showed that the number of microorganism in beras kencur and temulawak extract exceeded the maximum recommended standards and that its production did not meet the standard requirements for good production practices. Almost all standard of good production practices was violated. Factors influencing the high microbial content include : poor production practices (poor rhizome sortation and washing) , lack of hygienic practices during processing, no standardized processing procedures and no written standardized formula for both temulawak and beras kencur extract. and are also supported by the characteristic of the product that has a high pH, availability of nutrients, water activity and temperature (processing and storage), but also was inhibited by antimicrobial content. After implementation of the GJGPP, investigated samples show a decrease in microbial load. Product microbial load succeed to decrease near enough the maximum recommended standards and are negative in Salmonella sp. and Staphylococcus sp. Results on air sanitation before and after implementation showed a slight decrease, therefore environmental hygiene practices was not as critical as personnel hygiene. Application of good production practices in jamu gendong production has improved jamu gendong microbiological quality and safety
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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