Judul: Pembangkitan Biolistrik pada Plant-Microbial Fuel Cell Sebagai Sumber Energi Alternatif Menggunakan Tanaman Padi (Oryza Sativa)
Abstrak: Plant Microbial Fuel Cell (P-MFC) merupakan suatu inovasi pemanfaatan penguraian mikroorganisme pada tanaman yang aktif berfotosintesis untuk menghasilkan energi listrik. Prinsip kerja P-MFC adalah penguraian molekul karbohidrat (C6H12O6) pada akar tanaman dari hasil fotosintesis oleh bakteri mikroba secara anaerobik menjadi karbon dioksida, proton, dan elektron, P-MFC menghasilkan listrik dengan bantuan elektroda. Tujuan penelitian ini untuk mengetahui potensi energi listrik yang dihasilkan dari P-MFC dengan memanfaatkan proses fotosintesis dari tanaman padi dan bakteri Rizhosfer pada akar tanaman padi. Parameter listrik yang diuji berupa tegangan, arus, daya, dan power density dengan 6 variasi tanaman padi yaitu kontrol (tanpa tanaman padi), 2 bibit padi, 4 bibit padi, 6 bibit padi, 8 bibit padi, dan 10 bibit padi. Hasil Penelitian menunjukkan variasi 10 tanaman padi memiliki tegangan, arus, daya, dan power density tertinggi dibandingkan kelima variasi lainnya berturut-turut sebesar 209 mV, 2,09 mA, 436,81 mW, dan 109,2025 mW/cm2 pada jam 15.00 dengan resistansi 100 Ohm. Kata kunci: P-MFC, biolistrik, tanaman padi, fotosintesis, bakteri rizhosfer, Plant Microbial Fuel Cell is an innovative use of microorganisms in plants that are actively photosynthetic. The principle of P-MFC is the breakdown of carbohydrate molecules (C6H12O6) at the roots of photosynthesis by microbial bacteria anaerobically into carbon dioxide, protons, and electrons, PMFC produces electricity with electrodes. The purpose of this study was to determine the potential for electrical energy produced from P-MFC by utilizing the photosynthesis process of rice plants and rhizosphere bacteria on the roots of rice plants. The electrical parameters tested were voltage, current, power, and power density with six variations of rice plants, namely control, 2 seeds of rice plants, 4 seeds of rice plants, 6 seeds of rice plants, 8 seeds of rice plants, and 10 seeds of rice plants. The result showed that variation with 10 seeds of rice plants had the highest voltage, current, power, and power density compared to the other six variations, respectively, 209 mV, 2,09 mA, 436,81 mW, and 109,2025 mW/cm2 in the fifteenth hour with a resistance of 100 Ohms. Keywords: P-MFC, bioelectric, rice plants, photosynthesis, rhizosphere bacteria
Keyword: Plant-Microbial Fuel Cell, Bioelectric, rice plants, photosynthesis, rhizosphere bacteria

Judul: Evaluasi Pemupukan, Co-culture Mikrob, dan Salinitas terhadap Produksi Listrik Microbial Fuel Cell (MFC) pada Pertanaman Padi
Abstrak: Microbial Fuel Cell (MFC) adalah teknologi yang menggunakan mikrob eksoelektrogenik dan dapat diterapkan sebagai alternatif untuk menyediakan tenaga listrik tambahan. Penelitian ini bertujuan melihat pengaruh pemupukan, co-culture mikrob Staphylococcus saprophyticus ICBB 9554 dan Citrobacter sp. ICBB 9763, dan salinitas terhadap output listrik yang dihasilkan oleh sistem MFC pada pertanaman padi di dalam pot. Jenis MFC yang digunakan adalah MFC single chamber dengan elektroda karbon aktif. Tahapan penelitian terdiri dari uji sinergisme, pembuatan MFC, uji parameter tanah, persiapan tanam, penanaman, dan panen. Parameter yang diuji pada penelitian ini adalah output listrik dari MFC, pertumbuhan tanaman, dan parameter tanah yang terdiri dari sifat kimia dan biologi tanah. Hasil penelitian ini menunjukkan bahwa penambahan pupuk NPK 50%, co-culture mikrob, dan 100 mL NaCl disebar di ruang anoda memiliki nilai tegangan listrik tertinggi (646,33 mV) dan penambahan pupuk NPK 50%, tanpa co-culture mikrob, dan 1 L NaCl disebar di seluruh tanah memiliki nilai arus dan daya listrik tertinggi (0,404 mA dan 0,251 mW/MFC). Adanya perlakuan MFC tidak menganggu pertanaman padi. Nilai yang dihasilkan dari parameter listrik, tanaman, sifat biologi dan kimia tanah dipengaruhi oleh ketersediaan bahan organik tanah pada masing-masing perlakuan., Microbial Fuel Cell (MFC) is a technology that uses exoelectrogenic microbes and can be applied as an alternative to supply supplement electricity. This study aims to examine the effect of fertilization, co-culture microbes of Staphylococcus saprophyticus ICBB 9554 and Citrobacter sp. ICBB 9763, and salinity on the electrical output generated by the MFC system in rice planting in pots. The type of MFC used is a single chamber MFC with activated carbon electrodes. The research stages consist of synergism test, MFC making, soil parameter test, planting preparation, planting and harvesting. The parameters tested in this study were the electrical output of the MFC, plant growth, and soil parameters consisting of soil chemical and biological properties. The results of this study showed that the addition of 50% NPK fertilizer, the addition of co-culture microbes, and 100 mL of NaCl was spread in the anode had the highest electrical voltage value (646,33 mV) and the addition of 50% NPK fertilizer, without co-culture microbes, and 1 L NaCl was spread throughout the soil had the highest rated current and electric power (0,404 mA and 0,251 mW/MFC). The presence of MFC treatment did not interfere with rice cultivation. Values generated from the parameters of electricity, plant, biological and chemical properties of the soil are influenced by the availability of soil organic matter in each treatment.
Keyword: bahan organik, elektroda karbon aktif, output listrik

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