Judul: Karakteristik Permukaan Kayu Jati Biotrop Hasil Perlakuan Nanocoating TiO2 Sintesis melalui Uji Weathering
Abstrak: Kayu jati biotrop (Tectona grandis) merupakan salah satu jenis jati cepat tumbuh yang banyak diminati karena memiliki batang pohon dan tinggi bebas cabang yang baik. Akan tetapi, jati biotrop memilki ketahanan yang rendah. Perlakuan nanocoating titanium dioksida (TiO2) berbahan dasar varnish air dan minyak merupakan salah satu cara meningkatkan ketahanan serta kualitas permukaan kayu. Penelitian ini bertujuan untuk menganilisis pengaruh perlakuan surface coating berbahan dasar varnish air, varnish minyak dan campuran nano TiO2 terhadap karakteristik permukaan kayu jati biotrop sebelum dan setelah weathering. Uji karakteristik permukaan kayu meliputi perubahan warna (ΔE), kekasaran permukaan dan aktivitas fotokatalis. Hasil penelitian menunjukan bahwa setelah di weathering periode 4 bulan dapat meningkatkan perubahan warna dan kekasaran pada permukaan kayu. Perlakuan nanocoating TiO2 sintesis memberikan perubahan warna yang lebih rendah dibandingkan kayu kontrol serta dapat menghaluskan permukaan kayu. Perlakuan nanocoating TiO2 mampu mendegradasi metilen biru lebih besar dibandingkan kayu kontrol dalam aktivitas fotokatalis.
Keyword: biotrop teak, color change, nanocoating, photocatalyst, weathering

Judul: Analisis Karakteristik Permukaan Kayu Jati (Tectona grandis L.) dengan Aplikasi Nanocoating Titanium Dioksida terhadap Weathering
Abstrak: Kayu jati (Tectona grandis L.) cepat tumbuh memiliki karakteristik yang inferior dibandingkan dengan jati rotasi panjang seperti stabilitas dimensi dan keawetan yang rendah sehingga dapat membatasi penggunaannya terutama untuk aplikasi eksterior. Teknologi pelapisan (coating) menggunakan bahan yang bersifat melindungi dari paparan UV seperti nano titanium dioksida (TiO2) perlu dilakukan. Penelitian ini bertujuan untuk menganalisis pengaruh perlakuan coating (jenis dan konsentrasi nano TiO2) dan periode weathering terhadap kekasaran permukaan dan keterbasahan kayu jati (Tectona grandis L.). Bahan coating yang digunakan yaitu varnish berpelarut air dan varnish berpelarut minyak. Adapun nanocoating terbuat dari campuran nano TiO2 dan varnish dengan konsentrasi masing-masing 1%, 5%, dan 10%. Parameter yang diuji meliputi kekasaran permukaan dan keterbasahan. Hasil penelitian menunjukkan kayu yang diberi perlakuan coating varnish air menyebabkan permukaan kayu lebih halus. Penambahan nano TiO2 pada varnish air menurunkan keterbasahan kayu lebih baik dibandingkan varnish minyak. Kekasaran permukaan dan keterbasahan seluruh kayu jati mengalami peningkatan setelah weathering 2 dan 4 bulan., Fast growing Teak wood (Tectona grandis L.) has inferior wood characteristics compare to long rotation teak wood, such as poor dimensional stability and durability, which can limit its use especially for exterior aplications. This requires the use of coatings technology with substances like titanium dioxide nanoparticles (TiO2) that are made specifically to block UV radiation. This study aims to analyze the effects of coating treatment (coating type and consentration of nano TiO2) and weathering period on the surface roughness and wettability of teak wood. Both oil-based and water-based varnish are utilized as coating materials. Any nanocoating is formed of varnish and nano-sized TiO2 particles, and each is applied separately at concentrations of 1%, 5%, and 10%. Parameters studied consisted of surface roughness and wettability. The results shows that wood treated with a water-based varnish makes the wood surface smoother than oil-based varnish. The wettability of wood is improved more by the addition of nano TiO2 to a water-based varnish than oil-based varnish. After 2 and 4 months of weathering, the surface roughness and wettability of all treated wood increased.
Keyword: nanocoating, surface roughness, teak, TiO2, wettability

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