Judul: Cellulose Triacetate Membrane Based Optical Sensor (Optode) As Iron Detector in Water
Abstrak: Besi merupakan logam berat yang sering dijumpai sebagai pencemar peraian. Konsentrasi besi yang tinggi bersifat toksik bagi kesehatan manusia, sehingga perlu dipantau keberadaannya dalam air. Pendeteksian besi dalam air dilakukan dengan memanfaatkan sensor optik (optode). Penelitian bertujuan memfabrikasi optode berbasis membran selulosa triasetat dengan reagen selektif terhadap Fe (III). Optode difabrikasi dengan mencampurkan polimer selulosa triasetat, pemlastis (asam oleat dan asetofenon), alikuot-336, dan tiosianat sebagai reagen selektifnya. Kinerja membran diuji berdasarkan rentang kerja, linearitas, batas deteksi dan kuantitasi, presisi, serta akurasi. Kinerja membran menunjukkan respon yang linear pada rentang konsentrasi 0,1–4 mg/L dengan koefisien determinasi (R2) 0,9937, batas deteksi 0,0250 mg/L, batas kuantitasi 0,0757 mg/L, presisi keterulangan dengan simpangan baku relatif 3,31%, dan rerata akurasi 100,49%. Selektivitas optode baik terhadap ion pengganggu Cr(VI) dan Pb(II). Warna kompleks optode stabil sampai hari ke-10. Aplikasi pendeteksian besi dalam sampel air menunjukkan rerata konsentrasi sebesar 0,2541 mg/L dengan presisi dan akurasi yang baik.
Keyword: cellulose triacetate, iron, optode, thiocyanate, water

Judul: Pengembangan Membran Elektrode Optik Selulosa Triasetat untuk Deteksi Besi.
Abstrak: Besi merupakan logam berat yang dapat membahayakan kesehatan manusia. Penelitian ini bertujuan membuat membran elektrode optik (optode) dari selulosa triasetat yang mengandung reagen selektif terhadap ion Fe(III). Optode dipreparasi dengan melarutkan selulosa triasetat (CTA) dalam kloroform dan ditambahkan campuran asetofenon-asam oleat, alikuot 336, dan ion tiosianat. Kinerja optode dievaluasi berdasarkan rentang kerja, limit deteksi dan limit kuantitasi, presisi, akurasi, selektivitas, dan stabilitas. Kinerja terbaik optode terjadi pada rentang kerja 0.1-5 mg/L dengan koefisien determinasi 0.9951, limit deteksi 0.09 mg/L, dan limit kuantitasi 0.29 mg/L. Nilai akurasi rata-rata 99.80%, optode selektif untuk ion Fe(III) dari ion pengganggu Pb(II) dan Cr(VI), dan kompleks warna yang terbentuk stabil selama 11 hari. Dengan demikian, membran optode CTA dapat digunakan untuk deteksi besi dan hasilnya dapat diterima.
Keyword: besi, optode, selulosa triasetat, tiosianat

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