Judul: Pengaruh pemberian infusa daun papaya [Carica papaya l.] pada mencit [Mus musculus albinus] yang diinfeksi Plasmodium berghei
Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh pemberian infusa daun papaya (Carica papaya L.) pada mencit yang diinfeksi Plasmodium berghei. Pada penelitian ini digunakan sebanyak 30 ekor mencit putih (Mus musculus albinus) jantan dan betina dengan bobot rata-rata 25 gram. Penelitian ini menggunakan rancangan acak lengkap dengan tiga ulangan. Mencit dibagi dalam 5 kelompok perlakuan yaitu 1) kontrol positif (KP) yang diinfeksikan Plasmodium berghei tanpa pengobatan, 2) Sulfadoksin-Pirimetamin sebagai kontrol obat (KO), 3) kelompok PA1 (infusa daun Carica papaya L. dengan pengenceran 1x10²), 4) kelompok PA2 (infusa daun Carica papaya L. dengan pengenceran 1x10) dan 5) kelompok PA3 (infusa infusa daun Carica papaya L. dengan pengenceran 1x 10). Perhitungan parasit Plasmodium berghei melalui pengamatan ulas darah dengan mengunakan mikroskop pembesaran 1000x dan pengelolahan data menggunakan uji analisis sidik ragam (ANOVA)-SAS System dan Duncan Multiple Range Test. Pengamatan preparat ulas darah menunjukan bahwa rataan parasitemia mencit jantan selama sebelas hari pengamatan setelah infeksi menunjukkan bahwa kelompok perlakuan PA1 memiliki tingkat efektifitas paling tinggi dalam menekan pertumbuhan parasitemia (4,81%) sedangkan pada mencit betina tingkat efektifitas tertinggi terjadi pada kelompok perlakuaan PA3 (6,36%). Untuk jumlah kematian tertingi akibat infeksi Plasmodium berghei terjadi pada mencit betina…
Keyword: Malaria, Plasmodium berghei, Papaya leaves infusion

Judul: Gambaran Leukosit Pada Mencit Yang Diinfeksi Plasmodium berghei Dan Diberi Infusa Daun Papaya (Carica papaya Linn.)
Abstrak: This research was conducted to determine the effect of Carica papaya Linn. leaf infusion to the percentage of differential leucocyte mice that was infected by Plasmodium berghei. This research used laboratory animals such as male and female mice (Mus musculus albinus) that had been infected by P. berghei. Design of this research was completely randomized design with three replication. About 30 mice with an average weight of 25 g were divided into 5 groups that consists of 1) KNO (normal control), 2) KN (negative control group) was infected P. berghei, 3) PA1 group (C. papaya L. leaf infusion with dilutions of 1 x 10-2), 4) PA2 (C. papaya L. leaf infusion with dilution 1 x 10-4) and 5) PA3 group (C. papaya L. leaf infusion with 1 x 10-6). The results showed that neutrophil percentage in male mice was tend to higher than female mice and KN group. Monocyte and eosinophil percentage in male and female mice was tend to lower than KN group. Lymphocyte percentage in male and female mice was tend to higher than KN group. Basophil percentage was not influence in all groups.
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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