Update app.py

app.py

@@ -605,8 +605,8 @@ def load_default_files(force=False):
 
 # ============================================================
 # 6) FAKTOR WILAYAH (TOTAL) — hanya untuk faktor/target/pop/coverage
-#    UPDATE: total wilayah (pop_total & target_total_68) ditambah kontribusi POP_KHUSUS
-#            TANPA bikin kolom khusus baru (langsung dijumlahkan)
+# UPDATE: pop_total & target_total_68 wilayah ditambah data KHUSUS (POP_KHUSUS)
+#         TANPA ubah logika faktor (tetap min(n_total/target,1))
 # ============================================================
 
 def build_faktor_wilayah(
@@ -631,15 +631,16 @@ def build_faktor_wilayah(
         pop_field = "Pop_Total"
         name_field = "Kab_Kota_Label"
 
-        # khs (kab) -> pakai kab_key
-        khs = pop_khusus.copy() if (pop_khusus is not None and not pop_khusus.empty) else pd.DataFrame()
-        if not khs.empty and "kab_key" in khs.columns:
-            khs_kab = khs.groupby("kab_key", as_index=False).agg({
+        # agregat KHUSUS per kab_key (sum)
+        if pop_khusus is not None and not pop_khusus.empty and "kab_key" in pop_khusus.columns:
+            pk_kab = pop_khusus.groupby("kab_key", as_index=False).agg({
                 "Target68_Total_Jenis": "sum",
                 "Pop_Total_Jenis": "sum"
             }).set_index("kab_key")
         else:
-            khs_kab = pd.DataFrame().set_index(pd.Index([]))
+            pk_kab = pd.DataFrame().set_index(pd.Index([]))
+
+        pk_prov = None  # tidak dipakai
 
     elif "PROV" in kew_norm:
         key_col = "prov_key"
@@ -650,17 +651,19 @@ def build_faktor_wilayah(
         pop_field = "Pop_Total_Prov"
         name_field = "Provinsi_Label"
 
-        # khs (prov) -> agregasi dari pop_khusus ke prov_key
-        khs = pop_khusus.copy() if (pop_khusus is not None and not pop_khusus.empty) else pd.DataFrame()
-        if not khs.empty and "prov_key" in khs.columns:
-            khs_prov = khs.groupby("prov_key", as_index=False).agg({
+        # agregat KHUSUS per prov_key (sum)
+        if pop_khusus is not None and not pop_khusus.empty and "prov_key" in pop_khusus.columns:
+            pk_prov = pop_khusus.groupby("prov_key", as_index=False).agg({
                 "Target68_Total_Jenis": "sum",
                 "Pop_Total_Jenis": "sum"
             }).set_index("prov_key")
         else:
-            khs_prov = pd.DataFrame().set_index(pd.Index([]))
+            pk_prov = pd.DataFrame().set_index(pd.Index([]))
+
+        pk_kab = None  # tidak dipakai
 
     else:
+        # fallback: perlakukan seperti kab/kota
         key_col = "kab_key"
         label_col = "KAB_DISP"
         label_name = "Kab/Kota"
@@ -669,14 +672,15 @@ def build_faktor_wilayah(
         pop_field = "Pop_Total"
         name_field = "Kab_Kota_Label"
 
-        khs = pop_khusus.copy() if (pop_khusus is not None and not pop_khusus.empty) else pd.DataFrame()
-        if not khs.empty and "kab_key" in khs.columns:
-            khs_kab = khs.groupby("kab_key", as_index=False).agg({
+        if pop_khusus is not None and not pop_khusus.empty and "kab_key" in pop_khusus.columns:
+            pk_kab = pop_khusus.groupby("kab_key", as_index=False).agg({
                 "Target68_Total_Jenis": "sum",
                 "Pop_Total_Jenis": "sum"
             }).set_index("kab_key")
         else:
-            khs_kab = pd.DataFrame().set_index(pd.Index([]))
+            pk_kab = pd.DataFrame().set_index(pd.Index([]))
+
+        pk_prov = None
 
     base = df.groupby([key_col, label_col], dropna=False).agg(
         n_total=("Indeks_Dasar_0_100", "size"),
@@ -686,7 +690,7 @@ def build_faktor_wilayah(
     for _, r in base.iterrows():
         gk = r["group_key"]
 
-        # ===== ambil target/pop dari POP utama (kab/prov) =====
+        # --- ambil dari POP_KAB/POP_PROV (existing) ---
         if gk in pop.index:
             target_total = pop.loc[gk, target_field] if target_field in pop.columns else np.nan
             pop_total = pop.loc[gk, pop_field] if pop_field in pop.columns else np.nan
@@ -694,35 +698,25 @@ def build_faktor_wilayah(
         else:
             target_total, pop_total, nm = np.nan, np.nan, r[label_name]
 
-        # ===== UPDATE: tambah target/pop dari POP_KHUSUS (langsung dijumlah) =====
+        # --- TAMBAH KHUSUS (ini inti request kamu) ---
         add_target, add_pop = 0.0, 0.0
         if "PROV" in kew_norm:
-            if "khs_prov" in locals() and (gk in khs_prov.index):
-                add_target = khs_prov.loc[gk, "Target68_Total_Jenis"] if "Target68_Total_Jenis" in khs_prov.columns else 0.0
-                add_pop = khs_prov.loc[gk, "Pop_Total_Jenis"] if "Pop_Total_Jenis" in khs_prov.columns else 0.0
+            if pk_prov is not None and (gk in pk_prov.index):
+                add_target = pk_prov.loc[gk, "Target68_Total_Jenis"] if "Target68_Total_Jenis" in pk_prov.columns else 0.0
+                add_pop = pk_prov.loc[gk, "Pop_Total_Jenis"] if "Pop_Total_Jenis" in pk_prov.columns else 0.0
         else:
-            if "khs_kab" in locals() and (gk in khs_kab.index):
-                add_target = khs_kab.loc[gk, "Target68_Total_Jenis"] if "Target68_Total_Jenis" in khs_kab.columns else 0.0
-                add_pop = khs_kab.loc[gk, "Pop_Total_Jenis"] if "Pop_Total_Jenis" in khs_kab.columns else 0.0
-
-        try:
-            add_target = float(pd.to_numeric(add_target, errors="coerce") or 0.0)
-        except Exception:
-            add_target = 0.0
-        try:
-            add_pop = float(pd.to_numeric(add_pop, errors="coerce") or 0.0)
-        except Exception:
-            add_pop = 0.0
-
-        # jumlahkan (kalau NaN -> treat 0 dulu)
+            if pk_kab is not None and (gk in pk_kab.index):
+                add_target = pk_kab.loc[gk, "Target68_Total_Jenis"] if "Target68_Total_Jenis" in pk_kab.columns else 0.0
+                add_pop = pk_kab.loc[gk, "Pop_Total_Jenis"] if "Pop_Total_Jenis" in pk_kab.columns else 0.0
+
+        # amanin numeric
         t0 = float(pd.to_numeric(target_total, errors="coerce")) if pd.notna(target_total) else 0.0
         p0 = float(pd.to_numeric(pop_total, errors="coerce")) if pd.notna(pop_total) else 0.0
+        at = float(pd.to_numeric(add_target, errors="coerce")) if pd.notna(add_target) else 0.0
+        ap = float(pd.to_numeric(add_pop, errors="coerce")) if pd.notna(add_pop) else 0.0
 
-        target_total = t0 + add_target
-        pop_total = p0 + add_pop
-
-        target_vals.append(target_total)
-        pop_vals.append(pop_total)
+        target_vals.append(t0 + at)
+        pop_vals.append(p0 + ap)
         label_fix.append(nm)
 
     base[label_name] = label_fix
@@ -733,7 +727,7 @@ def build_faktor_wilayah(
     m = base["pop_total"].isna() & base["target_total_68"].notna() & (base["target_total_68"] > 0)
     base.loc[m, "pop_total"] = base.loc[m, "target_total_68"] / float(FALLBACK_TARGET_RATIO)
 
-    # faktor pakai target_total_68 yang SUDAH ditambah khusus
+    # logika faktor TIDAK DIUBAH
     base["faktor_penyesuaian"] = [
         faktor_penyesuaian_total(n, t)
         for n, t in zip(
@@ -750,7 +744,7 @@ def build_faktor_wilayah(
         )
     ]
 
-    # ====== UPDATE SESUAI PERMINTAAN (DISPLAY) ======
+    # ====== DISPLAY (sesuai permintaan awal kamu) ======
     base["target_total_68"] = pd.to_numeric(base["target_total_68"], errors="coerce").fillna(0).round(0).astype(int)
     base["pop_total"] = pd.to_numeric(base["pop_total"], errors="coerce").fillna(0).round(0).astype(int)
     base["coverage_total_%"] = pd.to_numeric(base["coverage_total_%"], errors="coerce").fillna(0.0).round(2)
@@ -758,7 +752,6 @@ def build_faktor_wilayah(
 
     return base
 
-
 # ============================================================
 # 7) AGREGAT WILAYAH × JENIS (Final pakai faktor wilayah)
 # ============================================================
@@ -1495,6 +1488,17 @@ def generate_word_report(wilayah, summary_jenis, agg_total, agg_jenis, analysis_
 # 15) CORE RUN
 # ============================================================
 
+def _empty_outputs(msg="⚠️ Data belum siap."):
+    empty = pd.DataFrame()
+    empty_fig = go.Figure()
+    return (
+        "",  # kpi_md
+        empty, empty, empty, empty, empty,
+        None, None, None, None, None,
+        empty_fig, empty_fig, empty_fig,
+        msg, "Analisis belum tersedia."
+    )
+
 def run_calc(prov_value, kab_value, kew_value, df_all, df_raw, pop_kab, pop_prov, pop_khusus, meta):
     try:
         if df_all is None or df_all.empty or df_raw is None or df_raw.empty:
@@ -1513,7 +1517,6 @@ def run_calc(prov_value, kab_value, kew_value, df_all, df_raw, pop_kab, pop_prov
             return _empty_outputs("Tidak ada data untuk filter ini.")
 
         # ==== PIPELINE BARU (KUNCI KONSISTENSI) ====
-        # UPDATE: faktor_wilayah sekarang menambahkan POP_KHUSUS ke target_total_68 & pop_total (total wilayah)
         faktor_wilayah = build_faktor_wilayah(df, pop_kab, pop_prov, pop_khusus, kew_value or "(Semua)")
         agg_jenis_full = build_agg_wilayah_jenis(df, faktor_wilayah, pop_khusus, kew_value or "(Semua)")
         agg_total      = build_agg_wilayah_total_from_jenis(agg_jenis_full, faktor_wilayah, kew_value or "(Semua)")
@@ -1540,7 +1543,6 @@ def run_calc(prov_value, kab_value, kew_value, df_all, df_raw, pop_kab, pop_prov
             cols_upto = [c for c in cols_upto if c in agg_jenis_full.columns]
             agg_jenis_view = agg_jenis_full[cols_upto].copy()
 
-
         # FILTER RAW DOWNLOAD (df_raw)
         raw = df_raw.copy()
         if prov_value and prov_value != "(Semua)":