Update app.py

app.py

@@ -1700,36 +1700,86 @@ with col_insights:
         st.info("Speed data not available for High-Speed Fatigue Analysis.")
 
     # 3. Shift Pattern Analysis
-    if col_shift and col_shift in df.columns:
-        shift_counts = df[col_shift].value_counts()
-        # shift_alerts_by_hour = df.groupby([col_shift, 'hour']).size().reset_index(name='alerts') # Tidak digunakan dalam tampilan ini
-        
-        st.markdown(f"**Shift Pattern Risk**")
-        for shift_val in shift_counts.index:
-            shift_pct = (shift_counts[shift_val] / len(df)) * 100
-            st.metric(f"Shift {shift_val} Alerts", f"{shift_counts[shift_val]}", f"{shift_pct:.1f}% of total alerts")
-            if shift_pct > 50:  # If one shift has more than 50% of alerts
-                st.warning(f"Shift {shift_val} has disproportionately high alerts ({shift_pct:.1f}%). Review shift scheduling and workload.")
-            else:
-                st.info(f"Shift {shift_val} alert distribution is acceptable ({shift_pct:.1f}%).")
-    else:
-        st.info("Shift data not available for Shift Pattern Analysis.")
+if col_shift and col_shift in df.columns:
+    shift_counts = df[col_shift].value_counts()
+    
+    st.markdown("**Shift Pattern Risk**")
+
+    shift_color = "#d32f2f"  # warna merah gelap
 
-    # 4. Operator Risk Profiling
-    if col_operator and col_operator in df.columns:
-        operator_alerts = df[col_operator].value_counts()
-        top_risk_operators = operator_alerts.head(5)  # Top 5 operators by alerts
+    for shift_val in shift_counts.index:
+        shift_pct = (shift_counts[shift_val] / len(df)) * 100
         
-        st.markdown(f"**High-Risk Operator Identification**")
-        for op_name, count in top_risk_operators.items():
-            op_pct = (count / len(df)) * 100
-            st.metric(f"Operator: {op_name}", f"{count} alerts", f"{op_pct:.1f}% of total alerts")
-            if op_pct > 5:  # If an operator has more than 5% of all alerts
-                st.warning(f"Operator {op_name} has high fatigue risk ({op_pct:.1f}% of alerts). Consider coaching or rest plan.")
-            else:
-                st.info(f"Operator {op_name} fatigue risk is within acceptable range ({op_pct:.1f}%).")
-    else:
-        st.info("Operator data not available for Operator Risk Profiling.")
+        # Metric-style card
+        st.markdown(
+            f"""
+            <div style="
+                padding: 12px 16px;
+                border-radius: 10px;
+                background-color: #f9f9f9;
+                border: 1px solid #ddd;
+                margin-bottom: 10px;
+            ">
+                <div style="font-size: 16px; font-weight: 600;">
+                    Shift {shift_val} Alerts
+                </div>
+
+                <div style="font-size: 28px; font-weight: 700;">
+                    {shift_counts[shift_val]}
+                </div>
+
+                <div style="font-size: 14px; font-weight: 700; color:{shift_color};">
+                    {shift_pct:.1f}% of total alerts
+                </div>
+            </div>
+            """,
+            unsafe_allow_html=True
+        )
+
+        # Risk Message
+        if shift_pct > 50:
+            st.warning(
+                f"Shift {shift_val} has disproportionately high alerts ({shift_pct:.1f}%). Review shift scheduling and workload."
+            )
+        else:
+            st.info(
+                f"Shift {shift_val} alert distribution is acceptable ({shift_pct:.1f}%)."
+            )
+else:
+    st.info("Shift data not available for Shift Pattern Analysis.")
+
+# 4. Operator Risk Profiling
+if col_operator and col_operator in df.columns:
+    operator_alerts = df[col_operator].value_counts()
+    top_risk_operators = operator_alerts.head(5)  # Top 5 operators by alerts
+
+    st.markdown("**High-Risk Operator Identification**")
+
+    # Warna berdasarkan ranking 1–5
+    colors = ["#d32f2f", "#e57373", "#ef9a9a", "#ffcdd2", "#ffe1e4"]
+
+    for idx, (op_name, count) in enumerate(top_risk_operators.items()):
+        op_pct = (count / len(df)) * 100
+        color = colors[idx] if idx < len(colors) else colors[-1]
+
+        # Teks normal untuk nama dan jumlah alert
+        st.markdown(f"**Operator:** {op_name}  \n**Alerts:** {count}")
+
+        # Hanya 'Share' yang berwarna sesuai ranking
+        st.markdown(
+            f"<span style='font-weight:600'>Share:</span> "
+            f"<span style='color:{color}; font-weight:700'>{op_pct:.1f}% of total alerts</span>",
+            unsafe_allow_html=True
+        )
+
+        # Risk message (tetap gunakan component Streamlit agar konsisten)
+        if op_pct > 5:
+            st.warning(f"Operator {op_name} has high fatigue risk ({op_pct:.1f}%). Consider coaching or rest plan.")
+        else:
+            st.info(f"Operator {op_name} fatigue risk is within acceptable range ({op_pct:.1f}%).")
+
+else:
+    st.info("Operator data not available for Operator Risk Profiling.")
 
 
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