Judul: Pengujian Sifat Fisik dan Antirayap Minyak Atsiri Daun dan Daging Buah Pala (Myristica fragrans Houtt) terhadap Rayap Tanah (Macrotermes gilvus)
Abstrak: Penelitian ini bertujuan untuk menganalisis sifat fisik dan sifat antira yap min yak atsiri yan g berasal dari daun dan dagin g buah pala (Myristica fragrans Houtt). Rendemen min yak atsiri daun dan daging buah pala yan g diperoleh dengan pen yulin gan uap (steam distilation) adalah sebesar 0.60% dan 0.33%. Uji sifat antira yap min yak atsiri daun dan dagin g buah pala dilakukan terhadap rayap tanah (Macrotermes gilvus) selama 7 hari pengamatan den gan variasi konsentrasi min yak dagin g dan daun buah pala sebesar 30, 60, dan 120 mg/ml. Hasil pengujian sifat fisik menunjukkan bahwa min yak atsiri daun dan dagin g buah pala berwarna kuning pucat, berbau khas min yak pala, den gan nilai indeks bias pada 20 ºC daun dan dagin g buah yaitu 1.4700 dan 1.4950, sementara itu nilai bobot jenis pada 20 ºC daun dan dagin g buah pala adalah sebesar 0.8730dan 0.8650. Hasil pengujian sifat antira yap menunjukkan bahwa min yak atsiri daun pala memiliki nilai LC50 lebih rendah yaitu sebesar 29.1 mg/ml dibandingkan min yak atsiri dagin g buah pala dengan nilai LC50 sebesar 35.3 mg/ml.
Keyword: LC50, Macrotermes gilvus, minyak atsiri, Myristica fragrans

Judul: Aktivitas Larvasida Minyak Atsiri Daun Dan Daging Buah Pala (Myristica Fragrans Houtt) Terhadap Aedes Aegypti
Abstrak: Penelitian ini bertujuan untuk menguji aktivitas larvasida terhadap nyamuk Aedes aegypti, serta menganalisis senyawa kimia minyak atsiri daun dan daging buah pala yang diperoleh dengan penyulingan uap (steam distillation). Rendemen minyak atsiri daun dan daging buah pala secara berturut-turut, yaitu 0.66% dan 0.30%. Uji akivitas larvasida menggunakan larva instar III nyamuk A. aegypti dilakukan selama 24 jam terhadap minyak atsiri daun dan daging buah pala yang berasal dari pohon yang sama. Konsentrasi minyak pala yang digunakan pada penelitian, yaitu 50 μg/mL, 100 μg/mL, 150 μg/mL, 200 μg/mL, dan 250 μg/mL. Kontrol negatif merupakan perlakuan tanpa penambahan minyak dan kontrol positif dengan menggunakan larvasida sintetis abate yang mengandung 1% Temefos. Hasil penelitian menunjukan bahwa aktivitas larvasida A. aegypti minyak atsiri daging buah pala lebih tinggi dibandingkan minyak atsiri daun pala dengan nilai LC50 133.8 μg/mL untuk minyak atsiri daun pala dan 110.1 μg/mL untuk minyak yang berasal dari daging buah pala. Analisis GCMS menunjukkan bahwa komponen senyawa kimia dalam minyak pala didominasi oleh α-pinen, sabinen, β-pinen, delta 3-caren, limonen, β-felandren, α-terpinolen, linalool, safrol, kroweasin, dan miristisin. Senyawa kimia seperti α-pinen, β-pinen, sabinen, limonen, safrol, kroweasin, dan miristisin diduga berperan sebagai larvasida terhadap A.aegypti.
Keyword: Aedes aegypti, larvasida, LC50, minyak atsiri, Myristica fragrans

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