Update app.py

app.py

@@ -1699,6 +1699,8 @@ with col_insights:
     else:
         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()
@@ -1707,10 +1709,31 @@ with col_insights:
         for shift_val in shift_counts.index:
             shift_pct = (shift_counts[shift_val] / len(df)) * 100
             # Ganti st.metric dengan HTML custom
-            st.markdown(f"""
-            <div style="font-size: 24px; font-weight: bold;">{shift_counts[shift_val]}</div>
-            <div style="color: red; font-size: 14px; margin-top: -5px;">↑ {shift_pct:.1f}% of total alerts</div>
-            """, unsafe_allow_html=True)
+            st.markdown(
+    f"""
+    <div style="
+        background-color:#fff9c4;
+        padding:12px 16px;
+        border-radius:10px;
+        border:1px solid #eee;
+        margin-bottom:10px;
+    ">
+        <div style="font-size:16px; font-weight:600;">
+            Shift {shift_val} Alerts
+        </div>
+
+        <div style="font-size:28px; font-weight:700; margin-top:4px;">
+            {shift_counts[shift_val]}
+        </div>
+
+        <div style="font-size:14px; font-weight:700; margin-top:-2px;">
+            <span style="color:#d32f2f;">↑ {shift_pct:.1f}% of total alerts</span>
+        </div>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
+
             if shift_pct > 50:
                 st.warning(f"Shift {shift_val} has disproportionately high alerts ({shift_pct:.1f}%). Review shift scheduling and workload.")
             else: