Update app.py

app.py

@@ -1702,54 +1702,35 @@ with col_insights:
     # 3. 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
+    shift_color = "#d32f2f"  # merah gelap
 
     for shift_val in shift_counts.index:
         shift_pct = (shift_counts[shift_val] / len(df)) * 100
-        
-        # Metric-style card (PASTIKAN unsafe_allow_html=True)
+
         st.markdown(
             f"""
-            <div style="
-                padding: 12px 16px;
-                border-radius: 12px;
-                background-color: #ffffff;
-                border: 1px solid #eee;
-                margin-bottom: 10px;
-                box-shadow: 0 1px 3px rgba(0,0,0,0.05);
-            ">
-                <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 style="padding:12px 16px; border-radius:10px; background-color:#fff; border:1px solid #eee; margin-bottom:10px;">
+                <div style="font-size:16px; font-weight:600; color:inherit;">Shift {shift_val} Alerts</div>
+                <div style="font-size:28px; font-weight:700; color:inherit;">{shift_counts[shift_val]}</div>
+                <div style="font-size:14px; font-weight:700;">
+                    <span style="color:{shift_color};">{shift_pct:.1f}% of total alerts</span>
                 </div>
             </div>
             """,
-            unsafe_allow_html=True   # <-- WAJIB ADA INI
+            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."
-            )
+            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}%)."
-            )
+            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()