This system is designed to validate the Waste Analysis and Characterization Study (WACS) data of MENRO Pandi by developing and applying linear models and time series analysis. It integrates data mining techniques using CRISP-DM to extract meaningful insights and improve waste prediction accuracy. The system also incorporates validation techniques for assessing the reliability of predictive models. To enhance accessibility and usability, a web dashboard is developed to visualize WACS data, predictive models, and statistical analysis results, enabling stakeholders to make data-driven decisions in waste management.
MENRO Pandi Leads the town’s environmental programs and ensures that waste management practices are sustainable and effective.
Local Government Units (LGUs)Work hand in hand with MENRO to create policies and provide support for cleaner and greener communities.
Researchers & AnalystsStudy and analyze data to guide better decisions for the environment and future projects.
Community & ResidentsPlay a vital role by practicing proper waste management and supporting eco-friendly initiatives in their daily lives.
MENRO Pandi WACS Reports
Historical and recent waste analysis data.
Environmental and Waste Management Studies
Supporting research and methodologies.
Government & LGU Records
Policies and compliance reports related to waste management.
Predicts future waste generation using ARIMA models, helping communities plan waste management strategies in advance.
Uses Linear Regression to estimate population growth, supporting effective allocation of resources.
Transforms raw data into interactive charts and graphs, making complex trends easier to understand and analyze.
Provides clear and real-time forecasts, giving residents easy access to important environmental insights.
Delivers timely alerts, advisories, and announcements when forecasted data indicates critical changes.
Assists policymakers and communities in creating eco-friendly plans by providing accurate and data-driven insights.
