Academic and Research Use Disclaimer
The analytics results, visualizations, predictive models, interpretations, and generated insights presented in this platform are intended solely for academic, educational, and research purposes as part of an MSIT thesis study. These outputs do not officially represent the views, policies, conclusions, or official reports of the Department of the Interior and Local Government or any participating Local Government Unit.
The portal implements a Multi-Model Predictive Analytics Framework integrating clustering, classification, and association rule mining to transform CSIS survey evidence into actionable insights for evidence-based governance and intelligent public service evaluation.
Descriptive Analytics
Visual summaries of citizen responses, demographics, and service engagement indicators.
Predictive Models
K-Means clustering, decision tree classification, and Apriori association rule mining.
Citizen Segmentation
Cluster respondents by socio-demographic and service engagement patterns.
Service Gap Analysis
Track awareness, availment, satisfaction, and need for government action.
Governance Support
Support planning, monitoring, accountability, and strategic resource allocation.
Research Objectives
- Identify socio-demographic and behavioral patterns among citizens.
- Segment respondents through clustering analysis.
- Predict citizen engagement and satisfaction using classification models.
- Discover hidden relationships among service indicators through association rule mining.
- Support data-informed planning, monitoring, and policy formulation.
Service Areas and SDG Alignment
The portal analyzes health, education, social welfare, governance and response, public works and infrastructure, environmental management, and economic and investment promotion.
SDG 3 Good Health
SDG 4 Quality Education
SDG 8 Decent Work
SDG 9 Innovation and Infrastructure
SDG 10 Reduced Inequalities
SDG 11 Sustainable Communities
SDG 16 Strong Institutions
SDG 17 Partnerships
Academic Context
This platform was developed as part of an MSIT thesis entitled: A Multi-Model Predictive Analytics Framework for Evaluating Citizen Satisfaction Using Clustering, Classification, and Association Rules.
Research proponent: Donald B. Salminao, MSIT student of Ateneo de Davao University.
Vision Statement
Transforming Citizen Feedback into Intelligent, Data-Driven, and Sustainable Governance for the Filipino People.