CSIS Evidence-to-Action Decision Support Prototype

Evidence-to-action recommendations generated from the active dataset and its refreshed analytical outputs, subject to LGU validation.

Decision Rules Summary

Select a row to review its recommendation, supporting evidence, and traceability path.

7 service-area rules
Rank Service Area Service Stage Priority Concern Signal Priority
1 Economic and Investment Promotion 5 cluster segments Awareness Economic and Investment Promotion awareness gap Awareness Gap is the strongest current signal for Organization,accreditation and training of tourism related concessions. (76.7%). 76.7% High
2 Public Works and Infrastructure Home-secure citizens with lower service awareness Awareness Public Works and Infrastructure awareness gap Awareness Gap is the strongest current signal for Information and reading center (70.7%). 70.7% High
3 Support to Education Younger or single citizens facing service-access gaps Availment Support to Education availment gap Availment Gap is the strongest current signal for Alternative Learning System and/or other Special Education Programs (64.8%). 64.8% High
4 Social Welfare Services Home-secure citizens requesting further LGU action Need for Action Social Welfare Services need for action Need for Action is the strongest current signal for Older Persons / Senior Citizens Program (60.7%). 60.7% High
5 Environmental Management Younger or single citizens requesting further LGU action Need for Action Environmental Management need for action Need for Action is the strongest current signal for Solid Waste Management (54.7%). 54.7% High
6 Health Services Younger or single citizens requesting further LGU action Need for Action Health Services need for action Need for Action is the strongest current signal for Free Basic Medicine or Low-Cost Medicine Program (52.4%). 52.4% High
7 Governance and Response Younger or single citizens requesting further LGU action Need for Action Governance and Response need for action Need for Action is the strongest current signal for Traffic Management (51.5%). 51.5% High
Selected Decision
Health Services Cluster 2 Need for Action

Prioritize barangay-level health follow-up for underserved Cluster 2 citizens.

Use targeted outreach and referral tracking where citizens report unmet health-service needs but low actual availment.

42% Strongest current service-gap signal
0.78 How reliably the model separates response groups (0 = weak, 1 = strong)
3 Linked analytical sources: clustering, Decision Tree, and Apriori
Observed concern D11 responses show the strongest need-for-action signal.
Group to review first The selected cluster has the strongest related concern signal.
Proposed next step Validate the finding with the responsible service office and LGU records.
Decision status: AI-assisted recommendation pending human review. The system organizes analytical evidence and proposes a planning response; it does not make or approve policy decisions. Confirm local context, feasibility, and responsible-office approval before implementation.

Traceability

Follow the selected recommendation from CSIS survey evidence to a proposed LGU action, or reverse the flow for an audit.

1 Survey evidence D9 and D11 service-stage responses.
2 Model evidence Cluster summary, Decision Tree metrics, and Apriori pattern.
3 Decision rule High need for action with low availment.
4 Proposed LGU action Barangay-level health follow-up for Cluster 2.
Human validation required. Confirm the proposed action using LGU records, service-office evidence, feasibility review, field context, and stakeholder approval.
Detailed Evidence-to-Action Review Environmental Management · 5 indicator records Sankey and evidence audit
Analytics -> Harmonization -> Human Review -> Action

Evidence-to-Action Review

Cross-stage, clustering, Decision Tree, and Apriori results are translated into proposed LGU actions. Recommendations remain subject to local validation, feasibility review, and approval.

Environmental Management: Priorities are generated from the active dataset's largest indicator-level service gaps. Segment labels identify the portal group with the strongest related concern signal.
Every decision-support record includes: rank, cross-stage result, clustering result, Decision Tree evidence, repeated service-stage pattern, recommended LGU action, priority, responsible office, evidence audit, and monitoring indicator.
Recurring Decision Tree predictors — exploratory consistency signal: MCA Dim2 · 5/5 models (100%) Highest Educational Attainment · 5/5 models (100%) Source of Information · 5/5 models (100%) MCA Dim1 · 4/5 models (80%) MCA DimMagnitude · 4/5 models (80%) Relationship to HH Head · 4/5 models (80%)
Repeated selection can identify factors for LGU investigation, but it does not overcome weak model discrimination, establish causality, or support individual targeting. Frequencies use available indicator models with at least one non-zero feature.
Cross-Service Benchmark

Predictor Coherence

Checks whether recurring Environmental Management predictors also recur across the wider CSIS classification workflow.

Open cross-service benchmark
Predictor Environmental Management recurrence Cross-service coverage Cross-Service Coherence
MCA Dim2 5/5 models (100%) 143 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Highest Educational Attainment 5/5 models (100%) 102 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Source of Information 5/5 models (100%) 119 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
MCA Dim1 4/5 models (80%) 133 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
MCA DimMagnitude 4/5 models (80%) 118 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Relationship to HH Head 4/5 models (80%) 71 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Source of Drinking Water 3/5 models (60%) 102 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Employment Status 3/5 models (60%) 77 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Civil Status 3/5 models (60%) 42 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
Age Group 2/5 models (40%) 72 models · 6 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
House Ownership 2/5 models (40%) 66 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
4Ps Beneficiary 2/5 models (40%) 55 models · 7 service areas · 4 stages System-wide coherent
The predictor recurs across at least three service areas and two service stages.
System-wide coherent means recurrence across at least three service areas and two service stages. Feature importance is unsigned, so this comparison checks recurrence and coverage—not relationship direction, causality, or suitability for individual targeting.
Dynamic indicator flow

Solid Waste Management

Hover over the Sankey nodes to audit how the four analytical evidence sources converge into an integrated interpretation, priority, proposed action, and monitoring measure.
Rank Cross-Stage Result Clustering Result Decision Tree Evidence Repeated Service-Stage Pattern Recommended LGU Action Priority Implementation and Monitoring
1 Solid Waste Management
Need for Action (54.7%)
Citizens who used the service still indicate a need for government action.
Awareness 86.9%; availment 83.0%; satisfaction 89.9%; need for action 54.7%.
 Young single student citizens (Segment B) (65.0%)
Young single student citizens (Segment B) has the highest concern signal at 65.0% for this indicator.
 Model quality
Needs more predictors: F1 57.8%, ROC AUC 53.8%. The model has difficulty separating respondents based on ROC AUC, recall, or F1.
Leading feature (exploratory)
MCA Dim2 (44.4% importance)
Treat as a validation cue, not a reliable explanation or causal factor.
 Respondents who were aware of the environment, and felt a need for further action, and were satisfied with the environment had a 87% likelihood of also availed the environment (Lift: 1.04). Support 32.5%, confidence 87.2%, lift 1.04. Prioritize follow-up validation with the service office and compare findings with LGU service records. Critical Environment and Natural Resources Office
Monitor: Reduction in need-for-action percentage
2 Community-based greening projects
Need for Action (52.4%)
Citizens who used the service still indicate a need for government action.
Awareness 76.8%; availment 65.6%; satisfaction 95.3%; need for action 52.4%.
 Married locally working men (Segment D) (54.6%)
Married locally working men (Segment D) has the highest concern signal at 54.6% for this indicator.
 Model quality
Needs more predictors: F1 52.8%, ROC AUC 53.8%. The model has difficulty separating respondents based on ROC AUC, recall, or F1.
Leading feature (exploratory)
Highest Educational Attainment (26.1% importance)
Treat as a validation cue, not a reliable explanation or causal factor.
 Respondents who were aware of the environment, and felt a need for further action, and were satisfied with the environment had a 87% likelihood of also availed the environment (Lift: 1.04). Support 32.5%, confidence 87.2%, lift 1.04. Prioritize follow-up validation with the service office and compare findings with LGU service records. Critical Environment and Natural Resources Office
Monitor: Reduction in need-for-action percentage
3 Clean-up Programs/Projects
Need for Action (52.3%)
Citizens who used the service still indicate a need for government action.
Awareness 82.5%; availment 86.6%; satisfaction 96.0%; need for action 52.3%.
 Young single student citizens (Segment B) (56.6%)
Young single student citizens (Segment B) has the highest concern signal at 56.6% for this indicator.
 Model quality
Needs more predictors: F1 50.5%, ROC AUC 51.6%. The model has difficulty separating respondents based on ROC AUC, recall, or F1.
Leading feature (exploratory)
Source of Information (28.7% importance)
Treat as a validation cue, not a reliable explanation or causal factor.
 Respondents who were aware of the environment, and felt a need for further action, and were satisfied with the environment had a 87% likelihood of also availed the environment (Lift: 1.04). Support 32.5%, confidence 87.2%, lift 1.04. Prioritize follow-up validation with the service office and compare findings with LGU service records. Critical Environment and Natural Resources Office
Monitor: Reduction in need-for-action percentage
4 Waste Water Management
Awareness Gap (50.2%)
Citizens may not yet know enough about this service.
Awareness 49.8%; availment 74.6%; satisfaction 93.8%; need for action 46.1%.
 Young single student citizens (Segment B) (40.8%)
Young single student citizens (Segment B) has the lowest positive response at 40.8% for this indicator.
 Model quality
Needs more predictors: F1 52.4%, ROC AUC 52.2%. The model has difficulty separating respondents based on ROC AUC, recall, or F1.
Leading feature (exploratory)
MCA Dim1 (26.5% importance)
Treat as a validation cue, not a reliable explanation or causal factor.
 Respondents who availed the environment had a 80% likelihood of also were aware of the environment, and were satisfied with the environment (Lift: 1.02). Support 66.9%, confidence 80.1%, lift 1.02. Strengthen information campaigns, barangay-level announcements, and direct citizen orientation. High Environment and Natural Resources Office
Monitor: Increase in awareness percentage
5 Air Pollution Control Program
Need for Action (49.9%)
Citizens who used the service still indicate a need for government action.
Awareness 66.1%; availment 83.4%; satisfaction 93.2%; need for action 49.9%.
 Young single student citizens (Segment B) (58.7%)
Young single student citizens (Segment B) has the highest concern signal at 58.7% for this indicator.
 Model quality
Needs more predictors: F1 41.7%, ROC AUC 48.1%. The model has difficulty separating respondents based on ROC AUC, recall, or F1.
Leading feature (exploratory)
MCA Dim1 (34.5% importance)
Treat as a validation cue, not a reliable explanation or causal factor.
 Respondents who were aware of the environment, and felt a need for further action, and were satisfied with the environment had a 87% likelihood of also availed the environment (Lift: 1.04). Support 32.5%, confidence 87.2%, lift 1.04. Prioritize follow-up validation with the service office and compare findings with LGU service records. High Environment and Natural Resources Office
Monitor: Reduction in need-for-action percentage
Priority method: Critical for satisfaction or need-for-action gaps of at least 50%; High for gaps of at least 40%; Medium for gaps of at least 20%; otherwise Low. Recommendations are evidence-based prompts—not automatic policy decisions.