Web-Based Wind Speed Forecasting System Using Prophet

The research undertaken has the central purpose of creating as well as applying a digital platform accessible through the internet, which is structured specifically to anticipate variations in wind velocity by employing the Prophet algorithm as the analytical framework. The system addresses the need for accurate and accessible forecasting tools in Medan, where highly variable wind patterns affect transportation, agriculture, and disaster mitigation. The research methodology consists of several stages including data collection from BMKG Medan, preprocessing through cleaning and aggregation of daily measurements into monthly averages, forecasting using the Prophet model, system development, and evaluation. Prophet was selected due to its ability to capture trend and seasonal components effectively with minimal parameter tuning. The system was developed using Laravel, MySQL, and Chart.js, integrating Prophet through Python to generate interactive visualizations and downloadable reports. The effectiveness of the predictive framework was measured by means of the Root Mean Square Error (RMSE = 0.19) and Mean Absolute Error (MAE = 0.15), validating the suitability of the method for producing consistent monthly forecasts of wind velocity. The system provides stakeholders such as disaster management agencies, marine operators, and agricultural planners with a practical platform for accessing accurate and timely forecasts. The findings further demonstrate the novelty of integrating Prophet forecasting with a web-based information system equipped with visualization and reporting features, thereby enhancing usability, accessibility, and decision-making support for regional meteorological applications.