Judul: Antioksidan Kulit Pisang (Musa paradisiaca) Pada Minyak Ikan Terhadap Stabilitas Oksidasi Dengan Katalis Panas Dan Cahaya
Abstrak: Minyak ikan maupun daging ikan memiliki kadar PUFA (Polyunsaturated Fatty Acid) yang sangat tinggi dan sangat sensitif terhadap reaksi oksidasi sehingga mudah mengalami ketengikan. Akibat reaksi oksidasi tersebut, minyak ikan maupun daging ikan mengalami penurunan nilai gizi, terjadi pembentukan flavor yang tidak diinginkan serta senyawa yang bersifat racun. Faktor panas dan cahaya merupakan faktor inisiasi yang paling umum terlibat dalam reaksi oksidasi selama pengolahan dan pengawetan ikan. Proses oksidasi ini dapat diminimalkan salah satunya dengan penambahan antioksidan. Penggunaan antioksidan sintetis dikhawatirkan memiliki efek samping terhadap kesehatan. Oleh karena itu, perlu digali pemanfaatan sumbersumber antioksidan alami yang dapat digunakan untuk pengawetan bahan pangan yang salah satunya dapat diperoleh dengan memanfaatkan kulit pisang. Berdasarkan hal tersebut, maka dilakukan penelitian dasar yang bertujuan untuk mempelajari pengaruh penambahan senyawa antioksidan yang diperoleh dari kulit pisang kepok dalam menghambat reaksi oksidasi minyak ikan yang disebabkan katalis panas dan cahaya. Senyawa antioksidan dari kulit pisang kepok diekstraksi menggunakan pelarut air, kloroform dan etil asetat. Ekstrak menghasilkan rendemen sebesar 0,02 % dengan total fenolik yang terkandung sebesar 123,09 mg/g ekstrak kering. Ekstrak menunjukkan adanya senyawa polifenol dan flavonoid setelah diuji secara kualitatif dengan menggunakan metode fitokimia. Uji TLC (Thin Layer Chromatography) dan scanning absorbansi ekstrak pada panjang gelombang 350-750 nm memperlihatkan bahwa ekstrak juga mengandung klorofil .
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Judul: Optimization of Kepok Banana Peel Extract (Musa paradisiaca L.) as an Antioxidant Ingredient
Abstrak: Limbah kulit pisang kepok (Musa paradisiaca) yang berpotensi sebagai antioksidan belum dimanfaatkan secara optimum. Penelitian ini bertujuan menentukan kondisi optimum maserasi kulit pisang kepok berdasarkan nisbah sampel:pelarut, konsentrasi pelarut, dan waktu maserasi menggunakan metode permukaan respons desain Box-Behnken untuk menghasilkan bahan antioksidan terbaik. Waktu maserasi merupakan variabel yang paling memengaruhi kapasitas antioksidan, kandungan fenolik dan flavonoid total dengan nilai p terkecil (<0,05) berdasarkan uji statistik Anova. Sementara itu, konsentrasi etanol merupakan variabel yang paling memengaruhi rendemen. Kondisi optimum ekstrak kulit pisang kepok berdasarkan analisis metode permukaan respons ialah kombinasi variabel nisbah sampel:pelarut 1:8,1, konsentrasi pelarut 72,9%, dan waktu maserasi 28,7 jam, dengan nilai prediksi respon, yaitu rendemen 33,9%, kapasitas antioksidan 6,9 AAE/g ekstrak, kandungan fenolik total 13,5 mg GAE/g ekstrak, dan kandungan flavonoid total 20,1 mg QE/g ekstrak., Kepok banana peel waste (Musa paradisiaca), which has the potential to be an antioxidant has yet to be optimally utilized. Thus, this study aims to determine the optimum condition of maceration of banana peels based on the samples:solvent ratio, solvent concentration, and maceration time using the Box-Behnken design response surface method to produce the best antioxidant ingredients. The maceration time was the variable that most affects antioxidant capacity, phenolic content, and total flavonoids, with the lowest p-value (<0.05) based on Anova statistical tests. Meanwhile, ethanol concentration was the variable that most affects the yield. Therefore, the optimum condition of banana peel extract based on the analysis of the response surface method was a combination of variable sample:solvent ratio of 1: 8.1, solvent concentration 72.9%, and maceration time of 28.7 hours, with a predicted response value, namely yield of 33.9%, the antioxidant capacity of 6.9 AAE/g extract, total phenolic content of 13.5 mg GAE/g extract, and total flavonoid content of 20.1 mg QE/g extract.
Keyword: antioxidant, Box-Behnken, kepok banana peel, optimization, response surface model

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