The materials in the skin care products have many types such as the whitening agent in the whitening cream. In general, researchers have conducted experiments to determine the effectiveness of such substances in the form of a single material in vitro. In practice, performance testing of material has conducted in Vivo that it is more than acceptable. In addition to use the materials altogether (synergistic) make higher performance or jump higher in a non-linear manner. The amount of these materials should be used in the right proportions. But to test the performance of materials in the real trial, each time it has a very high cost from volunteer, tracking, and duration of the experiment. We were unable to test the performance in several formulations. For this reason, the research objective is to develop algorithms to solve the problem of restrictions on such experiments to reduce time and cost. With a wide range of experimental design and use techniques to predict the outcome in early stage, then those results to design experiments and collect data. In this work, the effects of artificial neural networks (ANNs) to predict the effectiveness of the materials in whitening cream products were used incorporate with Genetic Algorithm (GA). In this article will experiment with simulated data from the experts as close to real data. To test the performance of the algorithm was developed and will extend the experimental results in the future. The algorithm of ANNs developed a multi-layer feed forward structure (4-13-1) with the lowest MSE is 6.00895e-4 and largest R2 is 0.979164. The best materials formulations optimized by GA were Arbutin=3%, Aloesin=0.658%, Niacinamide=0.007%, and Oxyresveratrol=0.993% that conduct lowest of 0.0823817 melanin value. Therefore, the algorithm developed in this study can be applied to develop the reality experiment in the future.