Judul: Resistensi Campylobacter sp. Asal Kulit Ayam Terhadap Antibiotik.
Abstrak: Daging ayam mudah terkontaminasi mikrob, salah satunya yaitu Campylobacter sp. Campylobacter sp. dapat menyebabkan penyakit pada manusia, yaitu campylobacteriosis. Pengobatan campylobacteriosis dilakukan menggunakan antibiotik golongan fluoroquinolone dan makrolida, namun Campylobacter sp. sudah resisten terhadap antibiotik tersebut. Tujuan penelitian ini adalah mengetahui tingkat resistensi Campylobacter sp. yang diisolasi dari kulit ayam terhadap beberapa jenis antibiotik yang digunakan di peternakan. Pengujian resistensi antibiotik dilakukan menggunakan metode Alfred and Kirby Bauer dengan mengukur diameter zona hambat yang terbentuk di sekeliling cakram antibiotik. Antibiotik yang digunakan adalah ceftazidime, cefotaxime, nalidixic acid, cotrimoxazole, tetracycline, kanamycin, ampicillin, dan amoxicillin. Hasil uji menunjukkan dari 21 isolat Campylobacter jejuni dan Campylobacter sp. resisten terhadap ceftazidime 66.7%, cefotaxime 85.7%, nalidixic acid 57.2%, cotrimoxazole 76.2%, tetracycline 66.7%, kanamycin 66.7%, ampicillin 76.2%, dan amoxicillin 66.7%. Hasil uji resistensi menunjukkan bahwa 19 dari 21 isolat Campylobacter sp. memiliki sifat multi drug resistance (MDR). Tingkat resistensi Campylobacter sp. terhadap antibiotik menunjukkan hasil yang tinggi terhadap hampir seluruh antibiotik, hal ini disebabkan penggunaan antibiotik yang tidak tepat di peternakan, tentu hal ini akan berdampak buruk terhadap kesehatan hewan dan manusia.
Keyword: antibiotik, Campylobacter sp., kulit ayam, resistensi

Judul: Isolasi dan Identifikasi Klebsiella sp. yang Resisten Antibiotik di Ayam Broiler dari Kabupaten
Abstrak: Klebsiella sp. adalah bakteri Gram-negatif yang biasanya ditemukan di flora mulut, kulit, usus hewan dan di lingkungan. Bakteri ini merupakan bakteri oportunistik yang menyebabkan infeksi pada hewan dan manusia. Sejak 10 hingga 20 tahun terakhir, Klebsiella sp. menjadi kebal terhadap berbagai jenis antibiotik. Resistensi antibiotik dapat menyebabkan kerugian ekonomi, biaya medis yang lebih tinggi, peningkatan morbiditas, dan mortalitas. Penggunaan antibiotik yang tidak tepat menyebabkan resistensi bakteri terhadap antibiotik. Tujuan dari penelitian ini adalah untuk mengisolasi, mengidentifikasi dan menentukan resistensi antibiotik Klebsiella sp. di ayam broiler dari kabupaten Cianjur. Uji resistensi antibiotik dilakukan dengan menggunakan metode difusi cakram Kirby- Bauer terhadap, ampisilin, eritromisin, tetrasiklin, oxytetracycline, asam nalidiksat, siprofloksasin, dan kloramfenikol. Hasil uji resistensi antibiotik mengacu pada Clinical and Laboratory Standard Institute (CLSI) 2017. Dari 30 sampel swab kloaka ayam yang diambil dari sebuah peternakan di Cianjur, didapatkan tujuh isolat Klebsiella sp. Hasil uji resistensi antibiotik menunjukkan bahwa ketujuh isolat Klebsiella sp. tahan terhadap ampisilin, eritromisin, dan tetrasiklin (100%); oxytetracycline (85,71%); asam nalidiksat (71,43%); siprofloksasin (57,14%); dan kloramfenikol (28,57%). Setiap isolat Klebsiella sp. menunjukkan resistensi multi-obat (MDR) terhadap setidaknya 4 dari 7 antibiotik yang diuji.
Keyword: resistensi antibiotik, ayam broiler, Klebsiella, resistensi multi-obat

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