Judul: Uji Aktivitas dan Studi Pustaka Karakterisasi Nanokomposit TiO2/ZnO/CuO Sebagai Fotokatalis Degradasi Zat Warna Rhodamin B
Abstrak: Nanokomposit merupakan material yang dibuat dengan menyisipkan nanopartikel dalam sebuah sampel material makroskopis. Metode sintesis nanokomposit TiO2/ZnO/CuO menggunakan metode modifikasi sol-gel. Penelitian bertujuan menyintesis nanokomposit TiO2/ZnO/CuO dengan berbagai komposisi, mengetahui kinerja nanokomposit TiO2/ZnO/CuO sebagai fotokatalis degradasi zat warna rhodamin B, dan melakukan kajian pustaka karakterisasi nanokomposit TiO2/ZnO/CuO. Hasil menunjukkan sintesis nanokomposit TiO2/ZnO/CuO dapat terbentuk dan dapat mendegradasi zat warna rhodamin B. Efektivitas fotokatalis dari nanokomposit TiO2/ZnO/CuO pada cahaya UV terukur sebesar 46% dan pada sinar tampak terukur sebesar 47%. Hasil kajian pustaka karakterisasi membuktikan bahwa ukuran, band gap, luas permukaan, morfologi, dan homogenitas mempengaruhi efektivitas fotokatalitik nanokomposit TiO2/ZnO/CuO.
Keyword: band gap, degradation, nanocoposites, photocatalyst, rhodamine B.

Judul: Sintesis Fotokatalis Komposit TiO2/ZnO/CuO untuk Fotodegradasi Pewarna Biru Bromotimol
Abstrak: Fotodegradasi merupakan proses peruraian suatu senyawa dengan bantuan energi foton. Biru bromotimol (BTB) merupakan salah satu pewarna sintetik yang termasuk dalam kelompok zat warna triarilmetana. Fotokatalis komposit TiO2/ZnO/CuO disintesis menggunakan metode sol-gel. Fotokatalis komposit TiO2/ZnO/CuO dikarakterisasi dengan spektroskopi FTIR dan menunjukkan adanya senyawa TiO2, ZnO, dan CuO. Aktivitas fotokatalitik dari komposit TiO2/ZnO/CuO memiliki efektivitas degradasi pada sinar tampak terukur sebesar 63% dengan waktu 60 menit pada suhu 25 oC. Aktivitas fotokatalitik dari komposit TiO2/ZnO/CuO juga memiliki efektivitas degradasi pada sinar UV terukur sebesar 74% dengan waktu 60 menit pada suhu 25 oC. Aktifitas fotokatalik komposit TiO2/ZnO/CuO lebih efektif pada zat warna yang memiliki konsentrasi kecil dibandingkan zat warna dengan konsentrasi besar baik pada sinar tampak maupun sinar UV. Hasil pengamatan menunjukkan adanya peningkatan persentase degradasi setelah fotodegradasi berlangsung. Hal ini diduga karena panjang gelombang komposit tumpang tindih dengan panjang gelombang larutan., Photodegradation is the process of decomposing a compound with the help of photon energy. Bromothymol blue (BTB) is one of the synthetic dyes that belongs to the triarylmethane dye group. TiO2/ZnO/CuO composite photocatalyst was synthesized using the sol-gel method. TiO2/ZnO/CuO composite photocatalyst was characterized by FTIR spectroscopy and showed the presence of TiO2, ZnO, and CuO compounds. The photocatalytic activity of the TiO2/ZnO/CuO composite was measured at visible light with degradation effectiveness of 63% at 60 minutes and 25 oC degrees. Photocatalytic activity of the TiO2/ZnO/CuO composite was also measured at UV degradation with an effectiveness of 74% at 60 minutes and 25 oC degrees. The photocatalytic activity of the TiO2/ZnO/CuO composite was more effective on dyes with small concentrations than dyes with large concentrations in both visible and UV light. The observations showed an increase in the percentage of degradation after photodegradation took place. This occurs due to interference from composite material whose wavelength may overlap with the wavelength of the solution.
Keyword: Bromothymol Blue, Photodegradation, Photocatalyst, TiO2/ZnO/CuO

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