Judul: Kadar Total Fenolik, Flavonoid, dan Aktivitas Inhibisi Tirosinase Fraksi Ekstrak Etanol Daun Sirih Merah (Piper crocatum Ruiz & Pav) Asal Solo
Abstrak: Sirih merah mengandung berbagai senyawa bioaktif yang dapat berperan sebagai agen depigmentasi dan juga berpotensi menghambat aktivitas enzim tirosinase. Penelitian ini bertujuan menentukan aktivitas inhibisi tirosinase melalui uji senyawa bioaktif fenolik dan flavonoid dari fraksi ekstrak etanol 70% daun sirih merah asal Solo. Metode ekstraksi dilakukan menggunakan maserasi dengan pelarut etanol 70%. Hasil ekstrak etanol 70% dilakukan fraksinasi bertingkat menggunakan tiga pelarut yang berbeda berdasarkan tingkat kepolarannya, yaitu nheksana, etil asetat, dan air. Kadar total fenolik diukur menggunakan metode FolinCiacalteu dan pengujian total flavonoid menggunakan pereaksi aluminium klorida. Berdasarkan hasil penelitian, diperoleh kadar total fenolik dan flavonoid tertinggi dari fraksi etil asetat dengan nilai 61,38 ± 1,16 mg GAE/g ekstrak dan 49,17 ± 1,63 mg QE/g ekstrak. Uji penghambatan tirosinase menggunakan substrat L-tirosin dan asam kojat sebagai kontrol positif menunjukkan ekstrak dan fraksi daun sirih merah dapat berperan sebagai inhibitor dengan % inhibisi tertinggi dihasilkan oleh fraksi air sebesar 51,53%.
Keyword: flavonoid, phenolic, red betel leave, tyrosinase

Judul: Kadar Total Fenolik, Flavonoid, dan Aktivitas Inhibisi Tirosinase dari Fraksi Ekstrak Sirih Merah (Piper crocatum Ruiz  & Pav) Asal Semarang
Abstrak: Sirih merah (Piper crocatum Ruiz & Pav) merupakan tanaman obat potensial yang dapat menyembuhkan berbagai jenis penyakit seperti diabetes mellitus, asam urat, hipertensi, dan kanker. Selain itu, daun sirih merah diketahui dapat mencegah dan menyembuhkan jerawat, dan mencerahkan kulit wajah kusam. Senyawa aktif pada sirih merah seperti fenolik dan flavonoid dapat berperan dalam menangani hiperpigmentasi dengan menghambat enzim tirosinase. Penelitian ini bertujuan menganalisis kadar total fenolik, flavonoid, dan aktivitas inhibisi tirosinase dari hasil fraksinasi ekstrak etanol sirih merah asal Semarang. Ekstraksi dilakukan dengan maserasi menggunakan etanol 70%, dan selanjutnya difraksinasi dengan 3 pelarut, yaitu n-heksana, etil asetat, dan air. Kadar total fenolik dan flavonoid tertinggi terdapat pada fraksi etil asetat yaitu sebesar 80.294 mg GAE/g dan 61.537 mg QE/g. Nilai penghambatan terhadap tirosinase terbesar juga terdapat pada fraksi etil asetat (65.86%). Aktivitas penghambatan tirosinase menunjukkan bahwa fraksi etil asetat memiliki nilai IC50 3470.53 ppm. Fraksi etil asetat daun sirih merah asal Semarang memiliki kemampuan sebagai inhibitor tirosinase lebih baik dibandingkan dengan fraksi n-heksana, fraksi air, dan ekstrak etanol 70%., Red betel (Piper crocatum Ruiz & Pav) is a potential medicinal plant that can cure various types of diseases such as diabetes mellitus, gout, hypertension, and cancer. Furthermore, red betel leaves are known to prevent and cure acne, and able to brighten facial skin. Active compounds in red betel such as phenolics and flavonoids are able to treat hyperpigmentation by inhibiting the tyrosinase. This research aimed to analyze total phenolics contents, flavonoids contents, and tyrosinase inhibitory activity from the fractionated ethanol extract of red betel from Semarang. The extraction was performed using maceration with 70% ethanol, and then fractionated with 3 solvents, n-hexane, ethyl acetate, and water. The highest total phenolics and flavonoids contents were found in the ethyl acetate fraction with values of 80.294 mg GAE/g and 61.537 mg QE/g. The highest inhibition value of tyrosinase was also found in the ethyl acetate fraction (65.86%). Tyrosinase inhibition activity showed that the ethyl acetate fraction has IC50 value of 3470.53 ppm. Therefore, the ethyl acetate fraction of red betel leaves from Semarang is proven to be a better tyrosinase inhibitor compared to the n-hexane fraction, water fraction, and 70% ethanol extract.
Keyword: phenolic, flavonoid, tyrosinase enzyme, red betel

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