Web-based learning system and simulation for time series seasonal adjustment

Time-series data is one of the data produced by the Badan Pusat Statistik (BPS). The time-series data has the potential to have a seasonal effect which can cause the analysis to be less accurate. Seasonal effects can be eliminated by making seasonal adjustments (SA). An understanding of SA is needed by BPS employees in analyzing time series data. Therefore we need a form of web-based learning that can be reached by all BPS employees. The goals of the system to accommodate the needs of users to get learning materials related to statistical material and provides convenience to users in implementing seasonal adjustments. An important feature that needed in this learning system is a simulation tool. The learning system is built using the SDLC method. In its development, the system uses the PHP programming language which is used as the main backend of web-based learning and R as a programming language in simulation applications. Data processing application simulation with seasonal adjustment method is built using the Jdemetra + package which is integrated with R Shiny. The evaluation results show that the system built was acceptable to the user with a SUS value of 73.8. The results showed that the participants can use the learning and simulation system as a pedagogical tool on SA learning.