Judul: Pengaruh Jenis Sampah Hayati Terhadap Karakteristik Eko-enzim
Abstrak: Eko-enzim merupakan cairan atau ekstrak enzim hasil proses fermentasi sampah hayati dengan penambahan substrat gula selama tiga bulan. Penelitian eko-enzim telah banyak dilakukan, namun pemanfaatan sebagai bahan cairan desinfektan, handsanitizer, serta obat kumur belum banyak meskipun secara empiris dipercaya dapat menangkal penyebaran Covid-19. Penelitian bertujuan mengkarakterisasi eko-enzim berdasarkan beberapa parameter, serta memperoleh karakter eko-enzim dari dua jenis sampah hayati yang berbeda. Rumus eko-enzim yaitu gula: bahan: air sebanyak 1: 3: 10. Analisis uji meliputi organoleptik, proksimat, total gula, kadar alkohol, total asam, asam askorbat, pH, total bakteri asam, serta identifikasi mikroba. Berdasarkan penelitian eko-enzim sayur mengandung total asam organik serta total bakteri asam yang tinggi pada minggu ke-12, sedangkan eko-enzim buah mengandung total gula dan kadar alkohol yang lebih tinggi serta pH larutan yang lebih asam. Mikroba eko-enzim teridentifikasi berasal dari kelompok kapang, khamir, dan bakteri. Peluang eko-enzim menangkal penyebaran Covid-19 disebabkan kandungan etanol serta asam organik yang saling bersinergi. Identifikasi mikroba dilakukan berdasarkan morfologi sehingga perlu uji patogenisitas untuk mengkonfirmasi keamanan produk eko-enzim. Oleh karena itu, eko-enzim masih sebatas untuk pemakaian luar.
Keyword: alcohol, biowaste, organic acids, Covid-19, eco enzymes

Judul: Analisis Karakteristik dan Uji Efektivitas Sabun Cair Cuci Tangan Ekoenzim
Abstrak: Ekoenzim adalah cairan yang dihasilkan dari fermentasi limbah dapur segar. Aplikasi ekoenzim sebagai produk belum banyak dilakukan. Adanya alkohol dan asam asetat dalam ekoenzim yang berfungsi sebagai desinfektan dan membunuh kuman dapat dimanfaatkan dalam pembuatan sabun cair cuci tangan. Bahan utama yang juga bisa dimanfaatkan adalah minyak jelantah. Penelitian ini bertujuan menganalisis kualitas dan efektivitas sabun cair cuci tangan ekoenzim berbasis minyak jelantah terhadap mikroba di tangan. Tahapan penelitian adalah karakterisasi ekoenzim, pemurnian minyak jelantah, formulasi sabun cair cuci tangan dengan penambahan ekoenzim 0%, 20%, 25%, dan 30% sebagai perlakuan. Tahapan selanjutnya adalah analisis karakteristik dan efektivitas sabun. Berdasarkan uji kualitas, sabun cair cuci tangan dengan konsentrasi ekoenzim 20% merupakan sabun formulasi yang memenuhi seluruh persyaratan mutu SNI 2588:2017. Berdasarkan uji efektivitas, sabun cair cuci tangan ekoenzim memiliki daya hambat lemah hingga kuat dan dibandingkan dengan sabun komersial, formulasi sabun dengan penambahan ekoenzim 30 % memiliki daya hambat terhadap bakteri Escherichia coli yang kuat dan lebih besar dari sabun komersial.
Keyword: alcohol, acetic acid, eco-enzymes, Escherichia coli, liquid hand soap, used cooking oil

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