Judul: Metode Kaczmarz untuk menyelesaikan sistem persamaan linear
Abstrak: A system of linear equations is often involved in science and engineering problems. There are many methods available for solving system of linear equations, both analytically and numerically. Kaczmarz method is one of iterative methods for solving such system. Orthogonal projections are used in this method. The sequence of approximate solutions generated by algorithm for this method is convergent for an arbitrary initial solution. A proof of the convergence is given. If the system of linear equations is consistent, then the sequence of approximate solutions converges to the exact solution. This shows that Kaczmarz method is a good method. Implementation of this method is done using MATLAB R2008b. Some systems of linear equations are generated, and then solved numerically using the program. The results show that the more iteration used in the solution approximation, the smaller norm of residual obtained.
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Judul: Metode generalized minimal residual(GMRES) dalam menyelesaikan sistem persamaan linear
Abstrak: Metode GMRES (Generalized Minimal Residual) adalah salah satu metode proyeksi subruang Krylov Kapan(r. Ar Aro) untuk menyelesaikan sistem persamaan linear tak-simetrik. Metode ini diperkenalkan oleh Saad dan Schultz tahun 1986. Cara kerja metode GMRES tampak pada algoritma GMRES. Pada algoritma GMRES terdapat 2 tahap dalam menyelesaikan masalah sistem persamaan linear yaitu tahap penentuan basis dan tahap penentuan solusi. Perbedaan yang nyata antara metode GMRES dengan metode yang lain (baik yang menggunakan bantuan subruang Krylov maupun yang tidak menggunakan subruang Krylov) adalah dalam mendapatkan solusi. Pada setiap iterasi algoritma GMRES, selain diperoleh basis subruang Krylov, dapat diperoleh pula estimasi besarnya residu tanpa menghitung solusi aproksimasi pada iterasi tersebut. Dari implementasi metode GMRES yang diterapkan pada matriks JPWH 991, tampak bahwa metode GMRES jauh lebih efisien dalam hal memori yaitu 177.768 bytes, sedangkan metode Gauss memerlukan memori minimal sebesar 982.081 bytes. Juga dalam hal banyaknya operasi floating point (dalam hal ini berhubungan dengan waktu yang digunakan) metode GMRES jauh lebih unggul dibandingkan dengan metode eliminasi Gauss.
Keyword: Generalized Minimal Residual Method, subspace projection methods, non-symmetric linear equations

Judul: Durability of Specific Immunoglobulin (Ig) Y Againts Influenza and Covid-19 in Sunscreen
Abstrak: The benefit of specific immunoglobulin Y (Ig Y) as an active ingredient in personal care products such as sunscreen has not been properly studied. Our study aims to evaluate the reliability of specific IgY against influenza and the COVID-19 virus in a sample sunscreen product. Specific IgY influenza and COVID-19 viruses were inserted in the sample sunscreen at two concentrations of 0.1% and 0.25%. Three treatments were observed: control (C) sunscreen without IgY, treatment 1 (T1) sunscreen with 0.1% IgY, and treatment 2 (T2) sunscreen with 0.25% IgY. Organoleptic observations were carried out to monitor changes in aroma, color, and texture, and sunscreen sampling was done every week for 6 weeks. The durability of IgY was evaluated using an enzyme-linked immunosorbent assay (ELISA) and a neutralization assay. Organoleptic observation from weeks 1 to 6 showed consistency in its aroma, color, and texture. Enzyme-linked immunosorbent assay and neutralization assay (NA) results of the T1 and T2 groups showed negative results except for sample T1 at week 5, which showed a positive result in the Influenza A ELISA. Based on the results, it seems that IgY concentrations of 0.1% or 0.25% were not optimal. However, this negative result might be due to low concentration of the IgY and the presence of beeswax, which inhibits IgY and causes it to dissolve in distilled water, thus preventing it from being detected in the assay.
Keyword: Immunoglobulin Y, Sunscreen, Influenza, COVID-19, Biological Activity