Judul: Peningkatan Elektrisitas Microbial Fuel Cell dengan Penempelan Isolat Bakteri pada Elektroda Dalam Limbah Cair Pemindangan Ikan
Abstrak: Microbial Fuel Cell (MFC) dapat membangkitkan listrik dari bahan organik dengan mendegradasi secara anaerob menjadi senyawa-senyawa yang membebaskan proton melalui bantuan bakteri. Penelitian ini bertujuan untuk mengetahui pengaruh penempelan isolat bakteri terhadap elektrisitas MFC yang dihasilkan, dan perubahan beban polutan yang dihasilkan limbah cair pemindangan ikan, serta kepadatan mikroba pada plat elektroda. Penempelan bakteri pada anoda dan katoda menggunakan isolat bakteri yang berbeda (anoda dengan Pediococcus acidilactici dan katoda dengan Staphylococcus warneri). Penelitian ini mempunyai empat tahap yaitu, penempelan bakteri pada elektroda, aklimatisasi lumpur aktif, desain MFC, dan penegukuran elektrisitas. Penelitian ini menggunakan empat perlakuan yang berbeda. Perlakuan AKL mendapatkan nilai elektrisitas rata-rata tertinggi dengan nilai tegangan 0.31±0.02 V, nilai arus listrik 3.28±0.66 mA, dan nilai daya 1.15±0.25 mW. Beban polutan pada parameter COD, BOD, dan TAN mengalami penurunan sebesar 57%, 38%, dan 92%.
Keyword: bacterial fixation, electrification, microbial fuel cell

Judul: Elektrisitas Microbial Fuel Cell dengan Jarak Elektroda yang Berbeda pada Media Limbah Cair Perikanan
Abstrak: Microbial Fuel Cell (MFC) merupakan alat yang digunakan sebagai penghasil tenaga listrik dan dapat dimanfaatkan sebagai pengolah limbah perikanan dengan bantuan bakteri eksoelektrogenik. Tujuan penelitian ini adalah mengidentifikasi pengaruh jarak elektroda terhadap elektrisitas pada pengolahan limbah cair industri perikanan dengan menggunakan teknologi MFC. Sistem MFC yang digunakan yaitu sistem MFC satu bejana. Jarak elektroda yang diberikan yaitu jarak 2 cm, 4 cm, dan 6 cm dengan elektroda yang digunakan yaitu stainless wire mesh yang dilapisi campuran kitosan dan karbon aktif. Jarak elektroda berpengaruh terhadap elektrisitas MFC pada media limbah rebusan ikan pindang. Hasil rata-rata nilai arus listrik selama 48 jam pengamatan secara keseluruhan mulai dari jarak 2 cm, 4 cm, dan 6 cm berturut-turut adalah 0,17±0,062 mA, 0,46±0,166 mA, dan 0,44±0,156 mA. Sedangkan nilai rata-rata tegangan listrik pada jarak 2 cm, 4 cm, dan 6 cm berturut-turut adalah 0,117±0,027 V, 0,337±0,069 V, dan 0,367±0,080 V. Hasil penelitian menunjukkan bahwa sistem MFC mampu menurunkan rata-rata BOD sebesar 20,5%, COD sebesar 30,41%, dan TAN sebesar 21,2% pada media limbah rebusan ikan pindang.
Keyword: jarak elektroda, limbah rebusan ikan pindang, microbial fuel cell

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