Judul: Isolasi dan Identifikasi Enterobacteriaceae dari Usap Mukosa Hidung Kuda
Abstrak: Kuda merupakan salah satu hewan dekat manusia yang memiliki risiko terkena infeksi Enterobacteriaceae. Tujuan penelitian ini adalah mengisolasi dan mengidentifikasi Enterobacteriaceae pada traktus respiratori kuda melalui morfologi dan metode biokimia. Sampel usap hidung yang diambil dari dua ekor kuda dibiakkan pada media agar darah, agar brain-heart infusion, dan agar Mac-Conkey. Karakter pertumbuhan koloni diamati. Mikromorfologi bakteri dari koloni murni diamati dengan pewarnaan Gram. Sebanyak 10 isolat representatif Enterobacteriaceae dipilih untuk uji biokimia meliputi oksidase, katalase, sulfide indole motility, methyl red-Voges Prosakuer, sitrat Simmon, urease Christensen, dan triple sugar iron agar. Analisa uji biokimia mengidentifikasi isolat-isolat sebagai Yersinia, Edwardsiella, dan Shigella.
Keyword: Enterobacteriaceae, kuda, usap hidung

Judul: Identification and Susceptibility Test of Escherichia coli Bacteria from Horses to Several Antibiotics
Abstrak: Escherichia coli merupakan mikroflora normal yang terdapat pada saluran cerna. E. coli seiring perkembangan waktu memiliki kemampuan resistan terhadap antibiotik tertentu dan dapat menyebarkan gen resistan ke bakteri lain. Permasalahan resistensi antibiotika merupakan masalah global. Informasi mengenai resistansi terhadap antibiotik pada kuda di Indonesia belum banyak dilakukan. Penelitian ini bertujuan mengidentifikasi bakteri yang ditemukan di saluran cerna pada kuda dan uji resistansi untuk mengetahui pola resistansi bakteri E. coli terhadap antibiotik yang dapat menunjang pengobatan pada kuda. Tahapan penelitian diawali dengan mengisolasi bakteri pada feses kuda menggunakan media agar EMBA dan MCA, lalu diidentifikasi dengan uji pewarnaan Gram serta beberapa uji biokimia. Isolasi dan identifikasi bakteri didapatkan 18 isolat bakteri E. coli, kemudian uji terhadap 6 antibiotik menunjukkan hasil masih peka atau sensitif terhadap antibiotik kloramfenikol (94%), amoksisilin (89%), gentamisin (83%), asam nalidiksat (78%), dan oksitetrasiklin (50%). Isolat resistan terhadap antibiotik sefotaksim (100%)., Escherichia coli is a normal microflora found in the digestive tract. Over time, E. coli can be resistant to certain antibiotics and can spread resistance genes to other bacteria. Overcoming antibiotic resistance is a global problem. Information regarding resistance to antibiotics in horses in Indonesia has not been widely carried out. This study aims to identify the bacteria found in the digestive tract of horses and test the resistance to determine the pattern of resistance of E. coli bacteria to antibiotics that can support treatment in horses. The research phase began with the isolation of bacteria from horse feces using EMBA and MCA agar media, then identified by Gram staining tests and several biochemical tests. Bacterial isolation and assistance obtained 18 isolates of E. coli bacteria, then tests on 6 antibiotics showed the results were still sensitive to the antibiotics chloramphenicol (94%), amoxicillin (89%), gentamicin (83%), nalidixic acid (78%), and oxytetracycline (50%). The isolates were resistant to cefotaxime (100%).
Keyword: antibiotic, Escherichia coli, horse, resistance

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