feat: upgrade recommended truck fleet capacity from 5T to 15T heavy compactor

app.py

@@ -465,13 +465,12 @@ async def predict_waste_volume(req: PredictionRequest):
                     paper_waste_ton=round(calibrated_volume*paper_r, 2), metal_waste_ton=round(calibrated_volume*metal_r, 2),
                     glass_waste_ton=round(calibrated_volume*glass_r, 2), textile_waste_ton=round(calibrated_volume*textile_r, 2),
                     other_waste_ton=round(calibrated_volume*other_r, 2),
-                    recommended_trucks=max(1, int(np.ceil(calibrated_volume/5))),
+                    recommended_trucks=max(1, int(np.ceil(calibrated_volume/15))),
                     risk_status=risk, event_info=info, hourly_breakdown=hourly
                 ))
         
         trucks = sum([r.recommended_trucks for r in results])
         msg = f"CRITICAL at {req.location}!" if max_risk == "CRITICAL" else f"WARNING at {req.location}." if max_risk == "WARNING" else "Normal conditions."
-        conf = 0.9828 if req.model_type == "gradient_boosting" else 0.92
         
         # Return accuracy score dynamically (Chronos is default 0.92, GBR shows training test score ~0.93)
         conf = 0.9325 if req.model_type == "gradient_boosting" else 0.92
@@ -483,7 +482,7 @@ async def predict_waste_volume(req: PredictionRequest):
                 logistics_plan=LogisticsPlan(
                     trucks_needed=trucks,
                     manpower=trucks*3,
-                    estimated_duration_hours=round(total_vol/5, 1),
+                    estimated_duration_hours=round(total_vol/15, 1),
                     efficiency_rate="85% (Optimal)"
                 )
             )
@@ -506,7 +505,7 @@ async def predict_waste_volume_csv(req: PredictionRequest):
         "Organic Waste (Tons)", "Plastic Waste (Tons)", 
         "Paper Waste (Tons)", "Metal Waste (Tons)",
         "Glass Waste (Tons)", "Textile Waste (Tons)",
-        "Risk Status", "Event Info", "Recommended Trucks (5T)"
+        "Risk Status", "Event Info", "Recommended Trucks (15T)"
     ])
     
     for r in res.data.prediction_results:
@@ -606,7 +605,7 @@ async def get_autopilot_data():
             raw_pred = dataset_mean # Fallback
             
         calibrated_volume = round(float(raw_pred * calibration_factor), 2)
-        trucks = max(1, int(np.ceil(calibrated_volume / 5)))
+        trucks = max(1, int(np.ceil(calibrated_volume / 15)))
         
         status = "CRITICAL" if calibrated_volume > config["critical_threshold"] else "WARNING" if calibrated_volume > config["warning_threshold"] else "SAFE"
         

frontend/app.js

@@ -468,7 +468,7 @@ function updateDashboardData(data, confScore, message) {
     updateMarkerRisk(selectedLocation, maxRisk);
     drawTransitRoute(selectedLocation);
 
-    if (statTrucks) statTrucks.innerHTML = `${data.logistics_plan.trucks_needed} <span class="unit">Trucks (5T)</span>`;
+    if (statTrucks) statTrucks.innerHTML = `${data.logistics_plan.trucks_needed} <span class="unit">Trucks (15T)</span>`;
 
     const startDateStr = results[0].date;
     const endDateStr = results[results.length - 1].date;
@@ -724,7 +724,7 @@ async function loadAutopilotFeed() {
             await new Promise(r => setTimeout(r, 500));
             
             autoVol.innerHTML = `${data.total_volume_ton.toLocaleString('en-US')} <span class="unit">Tons</span>`;
-            autoTrucks.innerHTML = `${data.total_trucks.toLocaleString('en-US')} <span class="unit">Trucks (5T)</span>`;
+            autoTrucks.innerHTML = `${data.total_trucks.toLocaleString('en-US')} <span class="unit">Trucks (15T)</span>`;
             
             autoRiskList.innerHTML = "";
             data.top_kecamatan.forEach((item, index) => {

frontend/index.html

@@ -264,7 +264,7 @@
                     </div>
                     <div class="panel stat-card">
                         <span class="card-label">RECOMMENDED FLEET</span>
-                        <span id="stat-trucks" class="card-value">0 <span class="unit">Trucks (5T)</span></span>
+                        <span id="stat-trucks" class="card-value">0 <span class="unit">Trucks (15T)</span></span>
                         <span class="card-meta">Logistics Fleet Suggestion</span>
                     </div>
                 </div>