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
64 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 1.05The strongest repeated service-stage pattern is: Respondents who availed the economic, and were aware of the economic had a 96% likelihood of also were satisfied with the economic (Lift: 1.05). This pattern was observed together 96.2% of the time for the eligible records.
The multi-model result for Economic and Investment Promotion points to awareness gap in Organization,accreditation and training of tourism related concessions. 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.