Budgeting System In Event Management Application Using Web-Based Genetic Algorithms

The increasing number of events usually formed a committee in small to large fields involving event organizers. In this study, the survey results were used to Telkom University students in Roadshow, Try Out and other committees. However, there are often problems in the implementation process caused by poor planning and supervision processes to have less clear financial statements. To anticipate this problem and create a web application-based event management application that provides appropriate budget recommendations. So, by using Genetics Algorithm is an optimization algorithm that can provide optimal results. This application is expected to help financial management reduce errors in the budgeting creation process and provide recommendations to users. Based on the test results, three experiments were carried out to see the optimal fitness value. In the first test, the densest optimal fitness value is between the +/- 18th generation out of a total of 50 generations. In the second experiment, the optimal fitness value is between the 20th generation to the 30th generation. In the last experiment, the optimal fitness value is between the 2nd generation to the 10th generation. This difference occurs because the random values used in each experiment are different. In this study, the genetic algorithm succeeded in recommending goods that match the maximum budget parameters of the division, indoor or outdoor category.