diff --git a/scripts/bigquery_aggregate_layer.py b/scripts/bigquery_aggregate_layer.py
index cbb97aa..07b02c2 100644
--- a/scripts/bigquery_aggregate_layer.py
+++ b/scripts/bigquery_aggregate_layer.py
@@ -6,8 +6,8 @@ UPDATED: Simpan 6 tabel ke fs_asean_gold (layer='gold'):
   - agg_pillar_by_country
   - agg_framework_by_country
   - agg_framework_asean
-  - agg_narrative_overview      (NEW)
-  - agg_narrative_pillar        (NEW)
+  - agg_narrative_overview
+  - agg_narrative_pillar
 """
 
 import pandas as pd
@@ -928,13 +928,21 @@ class FoodSecurityAggregator:
         self.logger.info(f"STEP 6: {table_name} -> [Gold] fs_asean_gold")
         self.logger.info("=" * 70)
 
-        # ASEAN-level Total framework rows, sorted by year
+        # ASEAN-level Total framework rows only, sorted by year
+        # PENTING: filter framework='Total' dulu sebelum apapun
         asean_total = (
             df_framework_asean[df_framework_asean["framework"] == "Total"]
             .sort_values("year")
             .reset_index(drop=True)
         )
 
+        # Buat lookup score per tahun untuk ambil prev_score yang akurat
+        # Tidak mengandalkan score - yoy_val karena floating point bisa drift
+        score_by_year = dict(zip(
+            asean_total["year"].astype(int),
+            asean_total["framework_score_1_100"].astype(float),
+        ))
+
         # Country-level Total framework rows (ranking + YoY per country)
         country_total = (
             df_framework_by_country[df_framework_by_country["framework"] == "Total"]
@@ -953,16 +961,19 @@ class FoodSecurityAggregator:
             yoy_val = float(yoy) if pd.notna(yoy) else None
 
             # -- Indicator counts per framework for this year ---------------
-            yr_ind    = ind_year[ind_year["year"] == yr]
-            n_mdg     = int(yr_ind[yr_ind["framework"] == "MDGs"]["indicator_id"].nunique())
-            n_sdg     = int(yr_ind[yr_ind["framework"] == "SDGs"]["indicator_id"].nunique())
+            yr_ind      = ind_year[ind_year["year"] == yr]
+            n_mdg       = int(yr_ind[yr_ind["framework"] == "MDGs"]["indicator_id"].nunique())
+            n_sdg       = int(yr_ind[yr_ind["framework"] == "SDGs"]["indicator_id"].nunique())
             n_total_ind = int(yr_ind["indicator_id"].nunique())
 
+            # -- prev_score diambil langsung dari lookup, bukan score - yoy_val
+            # Ini memastikan nilai konsisten 100% dengan tabel agg_framework_asean
+            prev_score = score_by_year.get(yr - 1, None)
+
             # -- YoY % -----------------------------------------------------
-            prev_score = score - yoy_val if yoy_val is not None else None
-            yoy_pct    = (
+            yoy_pct = (
                 (yoy_val / prev_score * 100)
-                if (yoy_val is not None and prev_score and prev_score != 0)
+                if (yoy_val is not None and prev_score is not None and prev_score != 0)
                 else None
             )
 
@@ -1306,7 +1317,7 @@ if __name__ == "__main__":
         _sys.stderr = io.TextIOWrapper(_sys.stderr.buffer, encoding="utf-8", errors="replace")
 
     print("=" * 70)
-    print("FOOD SECURITY AGGREGATION v9.0 — 6 TABLES -> fs_asean_gold")
+    print("FOOD SECURITY AGGREGATION-> fs_asean_gold")
     print(f"  NORMALIZE_FRAMEWORKS_JOINTLY = {NORMALIZE_FRAMEWORKS_JOINTLY}")
     print("=" * 70)