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: Surface Characteristics of Short Rotation Teak  Wood Chemical and Heat Modified and Weathering Tests
Abstrak: Modifikasi kimia dan panas merupakan alternatif untuk mengembangkan teknik peningkatan mutu kayu. Modifikasi kayu dengan bahan furfuril alkohol (FA) dan gliserol-maleat anhidrida (GMA) pada suhu 150 °C dan 220 °C terbukti dapat meningkatkan mutu kayu. Penelitian ini bertujuan menganalisis pengaruh modifikasi kimia dan panas terhadap karakteristik permukaan kayu jati rotasi pendek sebelum dan setelah weathering. Perlakuan yang dipakai dalam penelitian ini ialah impregnasi FA; impregnasi GMA diikuti dengan panas pada suhu 150 °C dan 220 °C; dan perlakuan panas suhu 220 °C. Hasil penelitian menunjukkan kayu yang diberi perlakuan panas menjadikan permukaan kayu yang lebih halus. Modifikasi kimia dan panas menyebabkan penurunan terhadap nilai energi bebas permukaan (Surface Free Energy-SFE). Nilai sudut kontak kayu jati perlakuan panas dan GMA suhu 220 °C lebih tinggi dibanding GMA suhu 150 °C. Cat alkid memiliki keterbasahan yang lebih baik daripada cat akrilik. Daya lekat cat alkid lebih baik dibanding dengan cat akrilik. Kayu jati rotasi pendek pada semua perlakuan mengalami peningkatan nilai keterbasahan setelah uji weathering selama 3 bulan., Chemical and heat modification are alternatives to develop wood quality improvement techniques. Modification of wood with furfuryl alcohol (FA) and glycerol-maleic anhydride (GMA) at 150 °C and 220 °C has been shown to improve wood quality. This study aims to analyze the effect of chemical and heat modification on the surface characteristics of short rotation teak before and after weathering. The treatments used in this study were impregnation with FA; impregnation with GMA followed by heat modification at 150 °C and 220 °C; and heat treatment at 220 °C. The results showed that heat treated wood made the surface of the wood smoother. Chemical and heat modifications caused the decrease in the value of surface free energy (SFE). The contact angle value of heat treated and GMA at 220 °C was higher than the GMA at 150 °C. Alkyd paints had a better wettability than acrylic paints. The bonding quality of alkyd paint also had a better than acrylic paint. Short rotation teak wood for all treatments increased in wettability value after 3 months of weathering.
Keyword: glycerol-maleic anhydride, heat modification, short rotation teak wood weathering, wood surface characteristics

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