SmartForecast: an interactive R Shiny Dashboard for rainfall forecasting in Subang

Forecasting plays a critical role in environmental planning, particularly in addressing rainfall variability that can impact urban development and flood preparedness. However, traditional forecasting tools often remain inaccessible to non-specialists due to their complexity. This innovation introduc...

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Bibliographic Details
Main Author: Bahrom, Suhaila
Format: Proceeding Paper
Language:en
Published: Academica Press Solution 2025
Subjects:
Online Access:http://irep.iium.edu.my/123003/7/123003_Smartforecast_an%20interactive.pdf
http://irep.iium.edu.my/123003/
https://zenodo.org/communities/apsproceedings/records?q=&l=list&p=1&s=10&sort=newest
https://doi.org/10.5281/zenodo.16788018
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Summary:Forecasting plays a critical role in environmental planning, particularly in addressing rainfall variability that can impact urban development and flood preparedness. However, traditional forecasting tools often remain inaccessible to non-specialists due to their complexity. This innovation introduces SmartForecast, a user-friendly forecasting dashboard developed using the Shiny package in R, specifically designed to model and predict monthly rainfall in Subang, Malaysia, using historical data from 2014 to 2023. Modelled using the SARIMA (4,1,0)(2,1,0)12 model chosen for its low RMSE and MAE, the dashboard transforms complex statistical forecasts into accessible visual and tabular outputs. Users can explore trends, forecast ranges, and descriptive statistics such as skewness, kurtosis, and the Jarque-Bera test. These features enhance interpretability, allowing policymakers, researchers, and the public to engage meaningfully with rainfall projections. The innovation supports transparent, evidence-based decision-making and promotes a culture of inclusive analytics in climate-sensitive sectors. By combining robust modelling with interactive design, SmartForecast serves as a practical tool for proactive environmental governance and sets the stage for scalable forecasting solutions in other contexts.