Judul: Sintesis hidrotermal nanopartikel karbon (C-dot) berfluoresens
Abstrak: Nanopartikel karbon (C-dot) berfluoresens merupakan nanomaterial berbasis karbon yang memiliki peluang aplikasi sangat luas. C-dot dapat disintesis dari berbagai sumber seperti asam sitrat, asam askorbat, dan limbah kulit jeruk. Tujuan penelitian ini adalah menyintesis dan mencirikan C-dot dari limbah kulit pisang dengan 4 perlakuan oksidasi yang berbeda. C-dot disintesis dari limbah kulit pisang dengan metode hidrotermal. Hasil yang diperoleh menunjukkan keempat sampel C-dot berpendar dibawah lampu UV 365 nm. Berdasarkan spektrum UV-Vis, tidak terdapat perbedaan yang signifikan pada pola serapan keempat sampel kecuali sampel yang dioksidasi dengan asam. Spektrum emisi keempat sampel memiliki pola yang sama dengan puncak emisi maksimum (503-514 nm) yang berbeda. Sampel yang dioksidasi dengan natrium hipoklorit menunjukkan intensitas fluoresens paling tinggi. Spektrum inframerah menunjukkan serapan COOH dan OH pada permukaan C-dot dan dapat dikembangkan sebagai sensor logam berat karena intensitas emisi C-dot menurun seiring dengan penambahan ion Hg(II).
Keyword: carbon nanoparticles, fluorescence, waste banana peels

Judul: Sintesis Nanopartikel Karbon (C-Dot) dari Air Kelapa sebagai Sensor Fluoresens Ion Fe3+.
Abstrak: Nanomaterial carbon atau C-Dots merupakan partikel nanomaterial 0 dimensi yang banyak digunakan sebagai material sensor untuk mendeteksi berbagai macam kandungan logam berat seperti logam Fe3+. C-Dots dibuat dari larutan air kelapa dan asam sulfat serta urea sebagai dopping dengan beragam konsentrasi. Selanjutnya larutan disintesis dengan metode microwave irradiation selama 4 menit dengan daya 400W. C-Dots dari air kelapa yang berhasil disintesis, dibuktikan dengan hasil analisis PSA, fluorometer, FTIR dan spektroskopi UV-Vis. Perbedaan ragam persen konsentrasi urea dalam sintesis C-Ddots menghasilkan karakteristik optik yang berbeda-beda. Penambahan urea menyebabkan kenaikan intensitas fluoresens. Panjang gelombang emisi mengalami pergeseran ke panjang gelombang lebih rendah (blue-shift). C-Dots akan mengemisikan warna biru ketika disinari dengan lampu UV. Hasil analisis PSA diketahui bahwa ukuran partikel cdots tergolong dalam kategori nanomaterial karena mempunyai rata-rata ukuran partikel sebesar 3.970 nm untuk sampel dengan kandungan urea 0% dan 6.416 nm nm untuk sampel dengan kandungan urea 8%.
Keyword: air kelapa, C-Dots, microwave irradiation, sensor fluoresens

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