Judul: Pengkajian aspek keamanan pangan pada warung makan di lingkar Kampus IPB Darmaga Bogor
Abstrak: Tujuan umum penelitian ini adalah untuk mempelajari keamanan pangan pada makanan dan air minum serta melihat praktek-praktek pengolahan makanan di warung makan-warung makan di Lingkar Kampus IPB Darmaga, Bogor. Tujuan khusus penelitian ini adalah: (1) mempelajari praktek-praktek penanganan makanan untuk mengidentifikasi tahap-tahap penting yang memungkinkan terjadinya kontaminasi (2) mengidentifikasi jenis makanan yang berisiko tinggi terhadap keracunan makanan oleh mikroba patogen seperti E. coli, Staphyloccocus aureus dan Sulmonella sp. (3) Evaluasi mutu mikrobiologis makanan (nasi, lauk pauk dan sayur) dan air minum yang tersedia di warung makan. Penelitian ini dilaksanakan di daerah Lingkar Kampus IPB Darmaga, Bogor dengan mengambil warung makan sebanyak 20 buah yang terdiri dari 2 kategori yaitu (1) warung kategori bersih dan (2) warung kategori kotor yang dipilih secara acak. Masing-masing kategori terdiri dari 10 warung makan. Penelitian dilaksanakan pada bulan September-Oktober tahun 2000. Dalam penelitian ini diambil sampel berupa makanan dan air minum dari warung makan-warung makan yang menjadi unit penelitian. Jenis makanan lauk pauk dan sayur diambil dari setiap warung makan, sedangkan untuk nasi dan air diambil dari beberapa warung makan yang mewakili tiap kategori.
Keyword: keamanan pangan

Judul: Studi keamanan mikrobiologis makanan di kantin asrama putra tingkat persiapan bersama Institut Pertanian Bogor
Abstrak: Tujuan umum penelitian ini adalah untuk mengevaluasi keamanan makanan di Kantin Asrama Putra TPB-IPB Dramaga ditinjau dari aspek mikrobiologis pada tingkat pedagang. Tujuan khusus untuk mengetahui penanganan makanan di kantin dan pengaruh waktu, lokasi kantin dan jenis makanan terhadap Total Mikroba, Escherichia coli juga adanya cemaran Salmonella- Shigella. Penelitian dilaksanakan pada bulan April sampai dengan Juni 2004 di Kantin Asrama Putra TPB-IPB dan Laboratorium Sanitasi dan Keamanan Pangan Departemen Gizi Masyarakat dan Sumberdaya Keluarga, Fakultas Pertanian, Institut Pertanian Bogor. Bahan yang dianalisis adalah nasi, tongkol balado dan sop (di kantin asrama) serta bubur ayam (di luar kantin asrama). Bahan lain adalah larutan NaCI 0,85%, alkohol 96%, spirtus, aquades, pereaksi Kovacks, aluminium foil, kapas, dan es batu. Peralatan yang digunakan adalah termos es, blender, mortar, bunsen, jarum ose, rak tabung reaksi, oven, inkubator, otoklaf, Darkfield Colony Counter serta peralatan gelas seperti cawan petri, tabung reaksi, pipet dan termometer. Media mikrobiologi yang digunakan adalah: Plate Count Agar (PCA), Eosin Methylene Blue Agar (EMBA), Selenity Cystine Broth (SCB), Salmonella Shigella Agar (SSA), Triple Sugar Iron Agar (TSIA) dan Sugar Indol Motility (SIM).
Keyword: mikrobiologis, keamanan makanan

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