Judul: Total Fenolik, Total Flavonoid, dan Aktivitas Antioksidan Ekstrak Teh Hijau, Teh Hitam, dan Teh Putih Kombucha
Abstrak: Kombucha tea is a fermented drink made from tea containing sugar by kombucha culture or SCOBY (Symbiosis Culture of Bacteria and Yeast). Total phenolic, total flavonoid and antioxidant activity tests were carried out to analyze and compare the antioxidant ability of kombucha made from green, black, and white tea to ward off free radicals. Samples were made into four types of kombucha, consisting of control kombucha (without tea), as well as green tea, black tea, and white tea kombucha. The highest antioxidant activity carried out using the DPPH method was obtained by black tea kombucha with percent inhibition and IC50 values of 88,29 ± 2,20% and 30,84 ± 1,34 μL/ml, respectively. Black tea kombucha also had the highest total phenolics and total flavonoids of 921,28 ± 38,08 mg GAE/L kombucha and 421,82 ± 24,05 mg QE/L kombucha respectively. The correlation results showed total phenolics and total flavonoids are directly proportional to the percent inhibition and inversely proportional to the IC50 value in kombucha. The characteristics of kombucha include pH and density which decrease after fermentation., Teh kombucha merupakan minuman fermentasi dari cairan teh yang mengandung gula oleh kultur kombucha atau SCOBY (Symbiosis Culture of Bacteria and Yeast). Uji total fenolik, total flavonoid, dan aktivitas antioksidan dilakukan untuk menganalisis dan membandingkan kemampuan antioksidan pada kombucha yang berasal dari teh hijau, teh hitam, dan teh putih dalam menangkal radikal bebas. Sampel dibuat menjadi empat jenis kombucha, terdiri dari kombucha kontrol (tanpa teh), serta teh hijau, teh hitam, dan teh putih kombucha. Aktivitas antioksidan tertinggi yang dilakukan dengan metode DPPH didapatkan oleh teh hitam kombucha dengan persen inhibisi dan nilai IC50 masing-masing sebesar 88,29 ± 2,20% dan 30,84 ± 1,34 μL/ml. Teh hitam kombucha juga memiliki total fenolik dan total flavonoid tertinggi masing-masing sebesar 921,28 ± 38,08 mg GAE/L kombucha dan 421,82 ± 24,05 mg QE/L kombucha. Hasil korelasi menunjukkan total fenolik dan total fenolik berbanding lurus dengan persen inhibisi dan berbanding terbalik dengan nilai IC50 pada kombucha. Adapun karakteristik kombucha berupa pH dan massa jenis yang berkurang setelah fermentasi.
Keyword: Antioxidant, Black tea, Green tea, Kombucha, White tea

Judul: Antioxidant Activity of Kombucha from Ganoderma lucidum and Camellia sinensis (L.) Kuntze Substrates with Various Fermentation Times
Abstrak: Kombucha merupakan produk minuman fungsional hasil fermentasi bakteri dan ragi. Penelitian ini bertujuan menentukan formula dan waktu fermentasi terbaik dari kombucha dengan substrat G. lucidum dan teh hijau berdasarkan kandungan fenolik, flavonoid, dan aktivitas antioksidan optimum. Sampel simplisia G. lucidum dan teh hijau dibuat menjadi 5 formula dengan perbandingan 1:0, 3:1, 1:1, 1:3, 0:1. Berdasarkan metode DPPH dan ferric reducing power (FRP), formula yang memiliki aktivitas antioksidan tertinggi didapatkan pada kombucha teh hijau (F5), dengan persen inhibisi dan IC50 DPPH paling optimum (rata-rata H-0 hingga H-17 sebesar 92,05% dan 22,302 µL/mL) serta potensi daya reduksi paling kuat di antara formula lainnya (absorbansi 0,523 pada 700 nm). Kandungan fenolik dan flavonoid pada F5 mencapai 479,729 mg GAE/L kombucha dan 95,766 mg QE/L kombucha. Sementara itu, kombucha G. lucidum (F1) menghasilkan fenolik dan flavonoid yang lebih rendah (nilai optimum 100,407 mg GAE/L kombucha dan 18,564 mg QE/L kombucha). F1 juga menunjukkan aktivitas antioksidan yang rendah, dengan rata-rata nilai inhibisi 32,45% dan IC50 DPPH 78,530 µL/mL serta potensi daya reduksi yang lebih lemah (absorbansi 0,150 pada 700 nm). Adapun variasi waktu fermentasi hampir tidak mempengaruhi aktivitas antioksidan DPPH kombucha., Kombucha is a functional beverage produced by bacterial-yeast fermentation. This study aimed to determine the best formula and fermentation time of kombucha with G. lucidum and green tea substrates for phenolic, flavonoid, and antioxidant content. Samples of G. lucidum and green tea simplisia were made into 5 formulas with ratios of 1:0, 3:1, 1:1, 1:3, 0:1. Based on the DPPH and ferric reducing power (FRP) methods, the formula with the highest antioxidant activity was found to be green tea kombucha (F5), with the most optimal percent inhibition and IC50 DPPH values (D-0 to D-17 average is 92.05% and 22.302 µL/mL) and the strongest reducing power potential among other formulas (absorbance 0.523 at 700 nm). The phenolic and flavonoid contents in F5 reached 479.729 mg GAE/L kombucha and 95.766 mg QE/L kombucha. Meanwhile, G. lucidum kombucha (F1) produced lower phenolics and flavonoids (optimum value of 100.407 mg GAE/L kombucha and 18.564 mg QE/L kombucha). F1 also showed lower antioxidant activity, with an average inhibition value of 32.45% and IC50 DPPH 78.530 µL/mL and weaker reducing potential (absorbance 0.150 at 700 nm). The variation of fermentation time barely affected the DPPH antioxidant activity of kombucha.
Keyword: antioxidant, Camellia sinensis, Ganoderma lucidum, kombucha

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