Update app.py

app.py

@@ -288,7 +288,7 @@ body {
 st.markdown(f"""
 <div class="header-container">
     <div class="header-title">
-        <h1>Safety Analysis and AI - Advanced Fatigue Analysis</h1>
+        <h1>Advanced Fatigue Analysis</h1>
         <p>Proactive Safety Intelligence for Mining Operations</p>
     </div>
     <div class="header-logo">
@@ -1159,7 +1159,7 @@ import plotly.graph_objects as go
 
 # =================== OBJECTIVE 5: Operator Fatigue Risk Gradient Dashboard =====================
 # ... (kode sebelumnya tetap sama) ...
-st.subheader("OBJECTIVE 5: See your team’s fatigue Fatigue Hazard Profile!")
+st.subheader("OBJECTIVE 5: See your team’s Fatigue Hazard Profile!")
 
 # Custom CSS — tetap seperti sebelumnya (sudah sesuai preferensi)
 st.markdown("""
@@ -1558,7 +1558,7 @@ else:
 
                 st.markdown(f"""
                 <div class="ai-insight-box">
-                    <div class="ai-insight-title">Risk Summary</div>
+                    <div class="ai-insight-title">Hazard Summary</div>
                     <ul style="padding-left: 20px; margin: 8px 0; line-height: 1.5;">
                         <li>{ob_insights[0]}</li>
                         <li>{ob_insights[1]}</li>
@@ -1591,7 +1591,7 @@ else:
 
                 st.markdown(f"""
                 <div class="ai-insight-box">
-                    <div class="ai-insight-title">Risk Summary</div>
+                    <div class="ai-insight-title">Hazard Summary</div>
                     <ul style="padding-left: 20px; margin: 8px 0; line-height: 1.5;">
                         <li>{coal_insights[0]}</li>
                         <li>{coal_insights[1]}</li>
@@ -1603,82 +1603,111 @@ else:
                 st.info("No HAULING COAL data for analysis.")
 
         # ===============================================================
-        # RECOMMENDATIONS — TIDAK DIUBAH SAMA SEKALI
+        # RECOMMENDATIONS — DIPERBARUI: 3 list per fleet, sesuai 3 poin Risk Summary
         # ===============================================================
         col_rec1, col_rec2 = st.columns(2)
 
-        def generate_recommendations(top_ob, top_coal):
-            rec = {}
+        with col_rec1:
             if not top_ob.empty:
                 w = len(top_ob[top_ob['slope'] > 0])
                 ot = len(top_ob[top_ob['slope'] == 0])
                 avg = top_ob['weekly_avg'].mean()
+                max_risk = top_ob['weekly_avg'].max()
+
+                # 3 rekomendasi, paralel dengan 3 poin Risk Summary
+                rec_list = []
+
+                # 1. Trend-driven action
                 if w > 5:
-                    r = "Prioritize fatigue intervention for operators with worsening trends."
-                    reason = "High proportion of deteriorating operators signals emerging fatigue risks."
-                elif ot > 4:
-                    r = "Validate data completeness — high One Time Event count may indicate reporting gaps."
-                    reason = "Operators with single-week data cannot yield reliable trend analysis."
-                elif avg > 8:
-                    r = "Review scheduling and rest protocols to reduce event frequency."
-                    reason = "Elevated average event rate increases cumulative fatigue exposure."
+                    rec_list.append("Conduct targeted fatigue risk assessments for operators with worsening trends (slope > 0).")
+                elif w > 0 and w <= 5:
+                    rec_list.append("Monitor worsening-trend operators weekly and schedule supervisor check-ins.")
+                elif w == 0 and len(top_ob[top_ob['slope'] < 0]) > 0:
+                    rec_list.append("Recognize improving operators — consider sharing best practices internally.")
                 else:
-                    r = "Maintain current protocols with targeted monitoring."
-                    reason = "Risk profile is stable; focus on sustaining safe practices."
-                rec['ob'] = r
-                rec['ob_reason'] = reason
+                    rec_list.append("Maintain current monitoring for stable trend profile.")
 
-            if not top_coal.empty:
-                w = len(top_coal[top_coal['slope'] > 0])
-                ot = len(top_coal[top_coal['slope'] == 0])
-                avg = top_coal['weekly_avg'].mean()
-                if w > 5:
-                    r = "Prioritize fatigue intervention for operators with worsening trends."
-                    reason = "High proportion of deteriorating operators signals emerging fatigue risks."
-                elif ot > 4:
-                    r = "Validate data completeness — high One Time Event count may indicate reporting gaps."
-                    reason = "Operators with single-week data cannot yield reliable trend analysis."
-                elif avg > 8:
-                    r = "Review scheduling and rest protocols to reduce event frequency."
-                    reason = "Elevated average event rate increases cumulative fatigue exposure."
+                # 2. One-Time Event follow-up
+                if ot > 0:
+                    rec_list.append(f"Re-engage {ot} <b>One Time Event</b> operators to verify data completeness and activity status.")
                 else:
-                    r = "Maintain current protocols with targeted monitoring."
-                    reason = "Risk profile is stable; focus on sustaining safe practices."
-                rec['coal'] = r
-                rec['coal_reason'] = reason
-            return rec
+                    rec_list.append("Trend analysis is reliable — all operators have multi-week activity.")
 
-        ai_rec = generate_recommendations(top_ob, top_coal)
+                # 3. Benchmark & sustain
+                if avg > 8:
+                    rec_list.append("Initiate immediate review of shift scheduling and rest-break compliance.")
+                elif avg > 5:
+                    rec_list.append("Conduct monthly fatigue KPI review using cohort average as baseline.")
+                else:
+                    rec_list.append("Sustain current protocols — risk level is within acceptable range.")
+
+                # Ensure exactly 3 items
+                while len(rec_list) < 3:
+                    rec_list.append("—")
 
-        with col_rec1:
-            if 'ob' in ai_rec:
                 st.markdown("### OB HAULER Recommendations")
                 st.markdown(f"""
                 <div class="recommendation-box">
                     <div class="recommendation-title">Action Plan</div>
-                    <div>{ai_rec['ob']}</div>
-                    <div class="recommendation-reason">AI Reasoning: {ai_rec['ob_reason']}</div>
+                    <ul style="padding-left: 20px; margin: 8px 0; line-height: 1.5;">
+                        <li>{rec_list[0]}</li>
+                        <li>{rec_list[1]}</li>
+                        <li>{rec_list[2]}</li>
+                    </ul>
                 </div>
                 """, unsafe_allow_html=True)
             else:
                 st.info("No OB HAULER recommendations.")
 
         with col_rec2:
-            if 'coal' in ai_rec:
+            if not top_coal.empty:
+                w = len(top_coal[top_coal['slope'] > 0])
+                ot = len(top_coal[top_coal['slope'] == 0])
+                avg = top_coal['weekly_avg'].mean()
+                max_risk = top_coal['weekly_avg'].max()
+
+                rec_list = []
+
+                # 1. Trend-driven action
+                if w > 5:
+                    rec_list.append("Conduct targeted fatigue risk assessments for operators with worsening trends (slope > 0).")
+                elif w > 0 and w <= 5:
+                    rec_list.append("Monitor worsening-trend operators weekly and schedule supervisor check-ins.")
+                elif w == 0 and len(top_coal[top_coal['slope'] < 0]) > 0:
+                    rec_list.append("Recognize improving operators — consider sharing best practices internally.")
+                else:
+                    rec_list.append("Maintain current monitoring for stable trend profile.")
+
+                # 2. One-Time Event follow-up
+                if ot > 0:
+                    rec_list.append(f"Re-engage {ot} <b>One Time Event</b> operators to verify data completeness and activity status.")
+                else:
+                    rec_list.append("Trend analysis is reliable — all operators have multi-week activity.")
+
+                # 3. Benchmark & sustain
+                if avg > 8:
+                    rec_list.append("Initiate immediate review of shift scheduling and rest-break compliance.")
+                elif avg > 5:
+                    rec_list.append("Conduct monthly fatigue KPI review using cohort average as baseline.")
+                else:
+                    rec_list.append("Sustain current protocols — risk level is within acceptable range.")
+
+                while len(rec_list) < 3:
+                    rec_list.append("—")
+
                 st.markdown("### HAULING COAL Recommendations")
                 st.markdown(f"""
                 <div class="recommendation-box">
                     <div class="recommendation-title">Action Plan</div>
-                    <div>{ai_rec['coal']}</div>
-                    <div class="recommendation-reason">AI Reasoning: {ai_rec['coal_reason']}</div>
+                    <ul style="padding-left: 20px; margin: 8px 0; line-height: 1.5;">
+                        <li>{rec_list[0]}</li>
+                        <li>{rec_list[1]}</li>
+                        <li>{rec_list[2]}</li>
+                    </ul>
                 </div>
                 """, unsafe_allow_html=True)
             else:
                 st.info("No HAULING COAL recommendations.")
-
-    except Exception as e:
-        st.error(f"Error in Top 10 Operator analysis: {str(e)}")
-        st.exception(e)
  # =================== OBJECTIVE 6: Automated Insights & AI Recommendations =====================
 st.subheader("OBJECTIVE 6: Instant Insights & Recommendations")