Judul: Utilization of Palm Shell Activated Charcoal as an Adsorbent on Biodiesel Dyes.
Abstrak: Adsorpsi zat warna pada biodiesel menggunakan arang aktif dari cangkang kelapa sawit dikaji dalam penelitian ini. Arang diaktifkan secara fisik pada suhu 800 °C selama 1 jam. Pencirian arang aktif yang dilakukan meliputi kadar air, kadar abu, daya adsorpsi terhadap iodin, daya adsorpsi terhadap biru metilena, memberikan hasil yang cukup baik bila dibandingkan dengan SNI, dan topografi permukaan menggunakan mikroskop elektron payaran. Hasil penelitian menunjukkan arang aktif memberikan kondisi optimum pada bobot adsorben 0.5 g selama 45 menit dengan nilai kapasitas dan efisiensi adsorpsi berturut-turut sebesar 103.64 mg/g dan 20.80%. Konsentrasi zat warna biodiesel turun dari 10 000 ppm menjadi 7 919.72 ppm, sedangkan angka setana biodiesel meningkat sebesar 9.85% dari 51.2 menjadi 56.8. Adsorpsi cangkang sawit menunjukkan model isoterm Freundlich sehingga diasumsikan terjadi secara multilayer atau banyak lapisan.
Keyword: 

Judul: Pembuatan Arang Aktif Tempurung Kelapa Sawit Sebagai Adsorben Dalam Pemurnian Biodiesel
Abstrak: Palm shell is one of solid waste from palm oil industries. To increase the added value and to reduce solid waste palm shell can be converted as activated charcoal. Application of activated charcoal could be done for purification process of biodiesel. Production of activated charcoal could be made through carbonization process at temperature of 450oC for five hours. The charcoal was soaked for 24 hours with the activator agent such as phosphoric acid activated with concentration of 15% and charcoal which was not soaked with phosphoric acid. Both of the charcoals were activated at temperature of 800oC with the variation time of 60, 90, and 120 minutes. The best quality of activated charcoal was the activation charcoal which were not soaked and activation time. The best quality of activated charcoal was the activation charcoal which were not soaked and activation time for 120 minutes with yield value of 56.5%, water content of 2.45%, volatile matter of 10.66%, ash content of 6.83%, fix carbon of 82.51%, adsorptive capacity of iodine 878.31mg/g, adsorptive capacity of benzene of 20,14%, and pH of 9.42. Crystalinity of activated charcoal of 39.89 %. Activated charcoal had been the standard of Standar Nasional Indonesia (SNI) 06-3730-1995. The ability of the best activated charcoal would be applicated for purification of biodiesel. Adding 3% of activated charcoal was better for purification of biodiesel so that was earned acid value of 0.22 mg KOH/g, pureness of 65.43%, pH of biodiesel of 7.29.
Keyword: 

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