Judul: Pencirian Minyak Sereh Wangi Mahapengiri (Cymbopogon winteranus Jowitt) Klon G1, G2, dan G3 Menggunakan Kromatograf Gas-Spektrometer Massa
Abstrak: Citronellal (Cymbopogon sp) oil is one of the Indonesia's essential oils export commodities. To maintain export quality, in 1989 three types of mahapengiri citronellal (C. winteranus Jowitt) G1, G2, and G3 superior clones were developed. In this experiment, the characteristics of major and minor chemical components within each clone were determined in order to develop formulations of oil fuel bioadditive. The study was started with steam distillation of citronellal leaves of clone G1, G2, and G3. The oil obtained were tested for the physicochemical properties, and the chemical compositions were analyzed with gas chromatograph-mass spectrometer. The results showed that the physicochemical properties of citronellal oil were in accordance with SNI 06-3987-1995. The major chemical constituents of citronellal oil were citronellal, citronellol, geraniol, limonene, β-caryophylene, and citronelyl acetate. The minor chemical constituents included D-germacrene, α-amorphene, endo-1-bourbonanol, geranyl acetate, linalool, δ-cadinene, elemol, β-elemene, (Z, E)-α-farnesene, α-cardinole, and α-humulene.
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Judul: A Study on the Withering Effect on the Yield and Quality of Distilled Citronella Oil
Abstrak: Indonesia merupakan salah satu negara penghasil minyak atsiri terbesar di dunia. Minyak atsiri adalah minyak beraroma khas dan bersifat mudah menguap (volatile), contohnya minyak nilam, minyak kenanga, minyak cengkeh, minyak kayu putih, minyak cendana, dan minyak serai wangi. Minyak serai wangi menjadi salah satu minyak atsiri yang menjadi komoditas ekspor unggulan Indonesia. Penelitian ini bertujuan mengkaji pengaruh pelayuan daun serai wangi terhadap rendemen dan mutu minyak serai wangi yang meliputi densitas, indeks bias, kelarutan dalam etanol 80%, warna, dan kandungan total sitronelal geraniol hasil proses penyulingan minyak serai wangi. Bahan yang digunakan adalah daun serai wangi yang diperoleh dari kebun serai wangi milik PT Harmonis Permaculture yang terletak di desa Karacak kecamatan Leuwiliang, sebanyak 3 kg untuk tiap perlakuan. Penelitian ini menggunakan rancangan acak lengkap faktorial dengan dua faktor yaitu lama pelayuan dan lama penyulingan. Perlakuan pelayuan yang diterapkan yaitu dilayukan selama 1, 2, dan 3 hari. Perlakuan lama penyulingan yang digunakan yaitu penyulingan selama 2 dan 4 jam sejak destilat keluar dari kondensor. Hasil penelitian menunjukkan bahwa perlakuan lama pelayuan dan penyulingan berpengaruh nyata (P<0,01) terhadap rendemen dan mutu minyak serai wangi. Hasil uji post-hoc Duncan menunjukkan adanya peningkatan rendemen dan mutu minyak yang signifikan secara statistik seiring dengan bertambahnya waktu pelayuan dan penyulingan. Hasil terbaik diperoleh dari perlakuan pelayuan selama 3 hari dan lama penyulingan 4 jam dengan rendemen 1,14%, densitas 0,891 g/cm3, indeks bias 1,4694, kelarutan dalam etanol 80% 1:2, warna kuning, sitronelal 43,24% dan total geraniol 21,73%. Secara keseluruhan mutu minyak serai wangi yang dihasilkan sudah sesuai SNI 06-3953-1995 untuk kebutuhan ekspor., Indonesia is one of the largest essential oil producing countries in the world. Essential oils are aromatic oils that are volatile, for example patchouli oil, kenanga oil, clove oil, eucalyptus oil, sandalwood oil, and citronella oil. Citronella oil is one of the essential oils which is Indonesia’s leading export commodity. This research aims to examine the effect of withering citronella leaves on the yield and quality of citronella oil which includes density, refractive index, solubility in 80% ethanol, color, and total citronellal geraniol content in the citronella oil as a result of distillation process. The sample used was 3 kg of citronella leaves obtained from PT Harmonis Permaculture located in Karacak village, Leuwiliang district for each treatment. This research used a completely randomized factorial design with two factors, namely duration of withering and distillation. The withering treatment applied was withering for 1, 2 and 3 days. The duration of distillation treatment used was distillation for 2 and 4 hours after the distillate came out from the condenser. The results showed that the duration of withering and distillation treatment had a significant effect (P < 0,01) on the yield and quality of citronella oil. Duncan's post hoc test results showed a statistically significant increase in oil yield and quality along with increasing withering and distillationduration. The best results were obtained from withering treatment for 3 days and distillation time of 4 hours with a yield of 1,14%, density 0,891 g/cm3, refractive index 1,4694, solubility in 80% ethanol 1:2, yellow color, citronellal 43,24% and total geraniol 21,73%. Overall,
Keyword: citronella oil, distillation, quality, withering, yield of citronella oil

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