Citizen segment evidence
AvailableThe clustering result identifies citizen segments and shows whether any segment has lower awareness, lower availment, lower satisfaction, or higher need for action.
Classification evidence
48 indicator modelsThe decision-tree classification uses citizen segment membership and profile variables as predictors. Most current indicator results are grouped as needs more predictors, which guides how strongly the result may be interpreted.
Association-rule evidence
Lift 1.02The strongest repeated service-stage pattern is: Respondents who felt a need for further action, and were satisfied with the public_works, and were aware of the public_works had a 95% likelihood of also availed the public_works (Lift: 1.02). This pattern was observed together 95.3% of the time for the eligible records.
The multi-model result for Public Works and Infrastructure points to awareness gap in Information and reading center as the main area needing attention. Clustering provides the citizen-segment lens, classification tests whether profile or segment variables help explain the service outcome, and association rules check whether the service-stage pattern repeatedly appears in the data.
Together, these findings show how the framework moves from citizen grouping, to prediction, to pattern discovery. The result should be treated as research-based decision support and validated with local service records, field context, and stakeholder review.
- Service-stage review: View descriptive service-stage results
- Citizen Segments: View segment profile and statistical support
- Classification: View predictor and model readiness evidence
- Association Rules: View repeated service-stage patterns
Use this page after reviewing the individual analytics modules. It consolidates the main evidence into one interpretation for planning, monitoring, evaluation, and field validation.