Judul: Combination of Turmeric Extract (Curcuma domestica val) and Noni (Morinda citrifolia) as Antidiarrhea
Abstrak: Kunyit dan mengkudu sudah digunakan sebagai pengobatan tradisional penyakit. Tanaman ini secara empiris digunakan untuk pengobatan diare. Akan tetapi, sejauh ini belum ada studi farmakologi aktivitas antidiare kombinasi ekstrak kunyit dan mengkudu. Tujuan penelitian ini adalah mengevaluasi secara ilmiah pengaruh kombinasi ekstrak kunyit dan mengkudu terhadap diare yang diinduksi minyak jarak pada mencit. Penelitian ini menggunakan 25 ekor mencit yang dibagi menjadi 5 kelompok. Kelompok dibagi menjadi kelompok kontrol negatif (Tween 80 1%), kelompok kontrol positif (Loperamid HCl) dan kelompok perlakuan kombinasi ekstrak kunyit dan mengkudu dosis 20 mg/kg BB, 40 mg/kg BB dan 80 mg/kg BB. Perlakuan dilakukan secara peroral. Parameter yang digunakan adalah proteksi intestinal (frekuensi defekasi mencit setiap 30 menit selama empat jam) dan transit intestinal (persentase lintasan penanda usus mencit). Hasil penelitian menunjukkan kombinasi ekstrak kunyit dan mengkudu dosis 20 mg/kg BB, 40 mg/kg BB dan 80 mg/kg BB memiliki efek antidiare dalam menurunkan frekuensi defekasi mencit dan menurunkan persentase lintasan penanda usus mencit. Dosis terbaik adalah 80 mg/kg BB. Hasil penelitian ini memberikan informasi ilmiah terhadap penggunaan kombinasi ekstrak kunyit dan mengkudu untuk pengobatan diare., Turmeric and noni have been recommended for several disease in folk medicine. They are empirically used for curing diarrhea. Nevertheless, no pharmacological studies of combination of turmeric and noni extracts have thus far evaluated for antidiarrheal activity. Our study aim was to evaluate scientifically the effect of combination of turmeric and noni extract against castor oil induced diarrhea models in mice. This study used 25 mice, they were divided into 5 groups. The groups are the negative control group (1% tween 80), the positive control group (loperamid HCl 0,26 mg/kg BW), and the treatment group combination of turmeric and noni extracts at dose of 20 mg/kg BW, 40 mg/kg BW, and 80 mg/kg BW respectively. The treatment was given orally. The parameters used for the evaluations are intestinal protection (frequency of defecation of mice every 30 minutes for four hours) and intestinal transit (percentage of mice intestinal marker trajectory). The results showed the combination of turmeric and noni extracts at a dose of 20 mg/kg BW, 40 mg/kg BW, and 80 mg/kg BW has an antidiarrheal effect in reduced the frequency of defecation of mice and decreasing the percentage of mice intestinal marker trajectories. The best dose is 80 mg/kg BW. The results obtained in this study give some scientific support to the use of a combination of turmeric and noni extract for the treatment of diarrhea.
Keyword: antidiarrhea, mice, noni extract, turmeric extract

Judul: Effectiveness of Combined Leaf Decoction of Keji Beling (Strobilanthes crispa (L.) Blume) and Kentutan (Paederia foetida) Plants as Antidiarrheals in Mice
Abstrak: Diare masih menjadi masalah kesehatan utama di negara berkembang. Keanekaragaman hayati yang tinggi di Indonesia, menjadi peluang penggunaan herbal sebagai salah satu solusi pengobatan diare. Herbal memiliki banyak kandungan nutrisi, mineral, dan senyawa aktif yang memiliki efek antidiare seperti tumbuhan keji beling dan kentutan. Penelitian ini bertujuan mengetahui efek dan konsentrasi terbaik antidiare dari kombinasi dekok daun keji beling dan kentutan. Kelompok perlakuan terdiri dari kelompok kontrol negatif, kelompok kontrol positif (loperamid) dan kombinasi dekok (konsentrasi 100%, 50%, 25%, dan 12,5%). Metode yang digunakan adalah proteksi dan transit intestinal pada mencit. Induksi diare menggunakan oleum ricini. Hasil penelitian menunjukkan bahwa kombinasi dekok kedua tanaman dapat menurunkan motilitas usus, mempertahankan konsistensi feses, dan memiliki nilai rasio transit intestinal yang baik. Konsentrasi 50% memiliki hasil terbaik., Diarrhea is still a major health problem in developing countries. The high biodiversity in Indonesia is an opportunity for the use of herbal plants as a solution for treating diarrhea. Herbal plants contain many nutrients, minerals, and active compounds that have anti-diarrheal effects, such as keji beling and kentutan plant. This study aims to determine the effect and the best concentration of antidiarrheals from the combination of leaf decoction of keji beling and kentutan. The group consisted of a negative control group, a positive control group (loperamide), and decoction combination (100%, 50%, 25%, and 12,5% concentrations). The method used is intestinal protection and transit in mice. Diarrhea is induced using oleum ricini. The results showed that the combination of decoction of the two plants could reduce intestinal motility, maintain stool consistency, and have a good intestinal transit ratio. The decoct concentration of 50% has the best results.
Keyword: diarrhea, keji beling, kentutan, intestinal protection, intestinal transit

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