Judul: Cara Diagnosa Kurap (Dermatophytosis) Pada Anjing
Abstrak: Diagnosa kurap dapt dipastikan dengan diagnosa mikologik. Pemeriksaam mikologik langsung merupakan cara yang sederhana dan praktis digunakan dalm praktek. Untuk mengidentifikasi species cendawan dermatofit digunakan pemeriksaan mikroskopik dari biakan slide dan pemeriksaan biakan yang mempelajari morphologi dan warna koloni cendawan tersebut.
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Judul: Kejadian Penyakit Kulit pada Anjing dan Kucing Akibat Infeksi Cendawan di Beberapa Klinik Hewan.
Abstrak: Anjing dan kucing merupakan dua jenis peliharaan yang yang paling sering dipelihara. Penampilan hewan peliharan harus selalu diperhatikan karena seringkali mengalami gangguan dan dapat berdampak pada infeksi yang lebih luas. Tujuan penelitian ini adalah mengetahui keragaman penyakit kulit yang disebabkan oleh infeksi cendawan dan agen lainnya pada anjing dan kucing. Penelitian menggunakan data sekunder yang berasal dari rekam medik periode 2010-2014 yang tersimpan di klinik yang diambil dari dua klinik hewan. Data primer diperoleh dari hasil identifikasi keberadaan kapang pada contoh kerokan kulit dan rambut pasien anjing dan kucing yang diambil dari 10 klinik hewan di Kota Bogor. Pemeriksaan makroskopik dilakukan terhadap koloni cendawan yang tumbuh di media pertumbuhan SDA dan SDA-m. Pemeriksaan mikroskopik dilakukan terhadap contoh kerokan kulit dan rambut yang ditetesi dengan KOH 10% dan terhadap struktur mikroskopik cendawan yang tumbuh di media pertumbuhan. Kasus infestasi ektoparasit merupakan kasus yang paling banyak didiagnosa dari anjing dan kucing yang dating ke klinik hewan dengan angka sebesar 30,00% pada anjing ras dan 45,58% pada kucing ras. Kasus dermatofitosis merupakan kasus kedua terbanyak yang dialami pasien, yaitu sebesar 25,71% pada anjing ras dan 14,28% pada kucing ras. Kapang Dermatofita tidak ditemukan pada contoh kerokan kulit dan rambut. Sejumlah cendawan saprofit dan kosmopolitan ditemukan dari contoh yang diperiksa
Keyword: penyakit kulit, infestasi ektoparasit, infeksi cendawan, anjing, kucing

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