Judul: Characteristics of Kenaf Fiber Charcoal (Hibiscus cannabinus L.) With Pyrolysis Carbonization
Abstrak: Serat kenaf merupakan serat yang cukup potensial untuk dijadikan sebagai bahan baku arang aktif melalui proses karbonisasi pirolisis. Proses ini lebih dipilih karena waktu proses yang digunakan relatif lebih singkat dan efisien dibandingkan dengan karbonisasi hidrotermal. Namun, ada beberapa hal yang harus dievalusi untuk menganalisis karakteristik arang pirolisis serat kenaf hasil karbonisasi pirolisis serta menganalisis pengaruh suhu dan waktu dalam proses karbonisasi pirolisis terhadap sifat arang serat kenaf dan daya jerap polutannya. Proses karbonisasi pirolisis dilakukan pada suhu 175 oC, 200 oC, 225 oC dengan waktu selama 3, 4, dan 5 jam. Karakteristik yang dianalisis dalam penelitian ini antara lain komponen kimia dan analisis proksimat dari serat kenaf, sedangkan dari arang yang dihasilkan, dianalisis rendemen, kadar air, kadar abu, kadar zat terbang, kadar karbon terikat, daya jerap iodin, dan daya jerap polutan (amonia, kloroform, formaldehida, dan benzena). Hasil penelitian menunjukkan interaksi antara suhu dan waktu karbonisasi pirolisis berpengaruh nyata terhadap kadar zat terbang, karbon terikat, daya jerap amonia dan daya jerap kloroform. Namun, interaksi antara suhu dan waktu karbonisasi pirolisis tidak memberikan pengaruh yang nyata pada daya jerap benzena, kadar air, dan kadar abu. Arang pirolisis terbaik didapatkan pada suhu 200oC selama 5 jam dengan daya jerap iodin sebesar 148,19 mg/g, Kenaf fiber is a fiber that has potential to be used as raw material for activated charcoal through the pyrolysis carbonization process. This process is preferred because the processing time used is relatively shorter and more efficient than hydrothermal carbonization. However, there are several things that must be evaluated to analyze the characteristics of the pyrolysis charcoal of kenaf fiber asa result of pyrolysis carbonization and to analyze the effect of temperature and time in the pyrolysis carbonization process on the characteristics of the kenaf fiber charcoal and its pollutant adsorption capacity. The pyrolysis carbonization process was carried out at temperatures of 175 oC, 200 oC, 225 oC for 3, 4, and 5 hours. The characteristics analyzed in this study included chemical components and proximate analysis of kenaf fiber, while the resulting charcoal was analyzed for yield, moisture content, ash content, volatile matter content, bound carbon content, iodine adsorption capacity, and pollutant adsorption capacity (ammonia, chloroform, formaldehyde, and benzene). The results showed that the interaction between temperature and time of pyrolysis carbonization had a significant effect on volatile matter, bound carbon, ammonia adsorption capacity and chloroform adsorption capacity. However, the interaction between temperature and time of pyrolysis carbonization did not have a significant effect on the adsorption capacity of benzene, moisture content, and ash content. The best pyrolysis charcoal was obtained at 200oC for 5 hours with an iodine adsorption capacity of 148.19 mg/g
Keyword: Arang pirolisis, daya jerap iodin, Daya jerap polutan, Karbonisasi pirolisis, Serat kenaf, Pyrolysis charcoal, Iodine adsorption capacity, Pollutant adsorption capacity, Pyrolysis carbonization, Kenaf fiber

Judul: Stem Characteristics of Kenaf (Hibiscus cannabinus L.) Hydrothermal Carbonized
Abstrak: Karbonisasi merupakan suatu proses untuk mendapatkan produk arang dengan suhu tertentu umumnya menggunakan suhu rendah dibawah 400 ℃ untuk menghasilkan arang hidro dan suhu tinggi sekitar 600 ℃ untuk menghasilkan arang aktif. Tujuan penelitian ini adalah menganalisis pengaruh suhu dan waktu dari proses karbonisasi hidrotermal terhadap batang kenaf serta menghilangkan hemiselulosa pada batang kenaf dengan proses hidrotermal. Penelitian ini menggunakan proses karbonisasi hidrotermal pada batang kenaf dengan suhu 130 ℃, 150 ℃, 170 ℃ dengan waktu 3 jam, 4 jam, dan 5 jam. Hasil penelitian ini menunjukkan karbon terikat, daya jerap polutan, dan daya jerap iodin arang hidro batang kenaf meningkat seiring kenaikan suhu dan waktu dibandingkan kontrol batang kenaf. Arang hidro batang kenaf terbaik didapat pada suhu 170 ℃ dalam waktu 3 jam dikarenakan total daya jerap iodin yang paling tinggi. Karbonisasi hidrotermal terbukti mampu mengurangi kandungan hemiselulosa., Carbonization is a process to get charcoal products with a certain temperature generally using low temperatures below 400 ℃ to produce hydro charcoal and high temperatures around 600 ℃ to produce activated charcoal. The objective of this study was to analyze the effect of temperature and time from the hydrothermal carbonization process on kenaf stems and to remove hemicellulose from kenaf stems using a hydrothermal process. This study used a hydrothermal carbonization process on kenaf stems with temperatures of 130 ℃, 150 ℃, 170 ℃ with 3 hours, 4 hours, and 5 hours. The results of this study showed that the bound carbon, pollutant adsorption capacity, and iodine adsorption capacity of hydro charcoal kenaf stems increased with increasing temperature and time compared to control kenaf stems. The best kenaf stems hydro charcoal was obtained at a temperature of 170 ℃ within 3 hours due to the highest total iodine adsorption capacity. Hydrothermal carbonization is proven to be able to reduce the hemicellulose content.
Keyword: Arang hidro, batang kenaf, daya jerap, karbonisasi hidrotermal, Adsorption capacity, hydro charcoal, hydrothermal carbonization, kenaf stems

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