Judul: Effect of OPEFB Filler on Rubber Matrix Foam Container Application in Air Mode Forest Fire Fighting
Abstrak: Kebakaran hutan kerap kali terjadi di Indonesia berulang-ulang setiap tahunnya. FC (Foam container) adalah Inovasi dalam penanganan kebakaran hutan mode udara yang memodifikasi metode WCB (water container ball) dengan mengganti isian air menjadi foam agent. Penelitian ini bertujuan membuat shell FC dari komposit sandwich TKKS - karet alam, karakterisasi dan pengujian-nya berdasarkan sistem pemadaman kebakaran hutan mode udara. Hasil uji menunjukan penambahan jumlah filler serat TKKS pada matrik karet alam ketebalan konstan dapat meningkatkan sifat mekanik dan ketahanan-nya terhadap pengaruh termal. Namun elastisitas biokomposit menurun seiring penambahan jumlah filler. Biokomposit memiliki potensi untuk dijadikan sebagai material shell FC, karena memenuhi syarat tidak rusak (pecah) saat benturan ringan namun dapat pecah saat bertumbukan dengan sasaran. Namun perlu dilakukan pengembangan pada metode penyambungan biokomposit untuk mendapatkan FC yang sesuai dalam aplikasi pemadaman kebakaran hutan mode udara.
Keyword: EFB, natural rubber, sandwich biocomposite, shell FC

Judul: The Effect of Oil Palm Empty Bunch (OPEB) Filler on the Mechanical Properties of Natural and Synthetic Rubber
Abstrak: Indonesia merupakan Negara dengan areal perkebunan yang luas. Salah satu komoditas perkebunan yang melimpah di Indonesia adalah karet dan kelapa sawit. Karet terbagi menjadi 2 jenis yakni karet alam dan karet sintetik. Keduanya memiliki sifat kepegasan pantul yang baik. Namun, dalam pemenuhan sifat mekanik baik karet alam maupun sintetik diperlukan adanya bahan pengisi (filler), salah satunya adalah serat Tandan Kosong Kelapa Sawit (TKKS). Penelitian ini bertujuan untuk menganalisa pengaruh konsentrasi filler serat woven TKKS dalam bentuk biokomposit tersusun laminar terhadap kekuatan mekanik karet (alam dan sintetis). Pembuatan biokomposit dilakukan dengan metode hot press. Uji mekanik matrik karet yakni tensile strength, elongation at break, dan rebound resilience menjukan sifat mekanik matrik terbaik adalah karet butyl. Uji impak biokomposit menunjukan sampel terbaik adalah sampel CNR-70, yakni biokomposit bermatriks karet alam dengan hardness 70 dan konsentrasi filler serat TKKS sebanyak 28 lembar., Indonesia is a country with a large plantation area. One of the abundant plantation commodities in Indonesia is rubber and oil palm. Rubber is divided into 2 types, namely natural rubber and synthetic rubber. Both of them have good reflective properties. However, in fulfilling the mechanical properties of both natural and synthetic rubber, a filler is needed, one of which is the fiber of the Empty Oil Bunches (EFB). This study aims to analyze the effect of the concentration of the OPEFB woven fiber filler in the form of a laminar composed biocomposite on the mechanical strength of rubber (natural and synthetic). The biocomposite was made by hot press method. Rubber matrix mechanical tests, namely tensile strength, elongation at break, and rebound resilience showed that the best matrix mechanical properties were butyl rubber. The biocomposite impact test showed that the best sample was the CNR-70 sample, namely the biocomposite with a natural rubber matrix with a hardness of 70 and a concentration of OPEFB fiber filler as much as 28 sheets.
Keyword: biocomposite, filler, rubber, OPEFB

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