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 that transforms CSIS survey evidence into dashboard insights for evidence-based governance and service delivery review.
Survey Evidence
Socio-demographic profile, housing profile, service-area responses, perception of corruption, citizen attitude toward the LGU, and overall rating.
Data Preparation
Data entry pipeline, raw file validation, data cleaning, generated CSIS output files, and active data source selection.
Analytics Models
K-Means clustering, decision tree classification, and Apriori association rule mining.
Dashboard Insights
Citizen profile baseline, citizen segments, classification insights, service pattern insights, and service review priorities.
Decision Support Output
Interactive visual dashboard and analytics report outputs for planning, monitoring, and policy formulation.
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.
Dashboard Scope and Service Areas
The dashboard presents service delivery review for health services, support to education, social welfare services, governance and response, public works and infrastructure, environmental management, and economic and investment promotion.
Perception of corruption, citizen attitude toward local government, and citizen overall rating are presented in the Governance Evidence module because they support interpretation of citizen trust and overall LGU performance.
Service Indicators and SDG Alignment
Service indicators are organized around Awareness, Availment, Satisfaction, and Need for Action.
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 and Service Delivery Performance of Local Government Units.
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.