Update app.py

app.py

@@ -1560,76 +1560,87 @@ ATURAN:
     except Exception as e:
         return f"⚠️ Error saat memanggil LLM: {repr(e)}"
 
-def generate_word_report(wilayah: str, summary_jenis: pd.DataFrame, agg_total: pd.DataFrame, analysis_text: str):
+def generate_word_report(wilayah, summary_jenis, agg_total, agg_jenis, analysis_text):
     doc = Document()
     doc.add_heading(f"Laporan IPLM — {wilayah}", level=1)
 
+    # =========================
+    # Ringkasan Dashboard (KPI utama)
+    # =========================
     doc.add_heading("Ringkasan Dashboard", level=2)
+
     k = compute_dashboard_kpis(summary_jenis)
-    doc.add_paragraph(f"Indeks IPLM FINAL (Disesuaikan): {k['final_all']:.2f}")
-    doc.add_paragraph(f"Indeks Dasar (Tanpa Penyesuaian): {k['dasar_all']:.2f}")
+    doc.add_paragraph(
+        f"Indeks IPLM FINAL (Disesuaikan): {k['final_all']:.2f} "
+        f"(rata-rata 3 jenis: sekolah, umum, khusus; tetap ÷3)"
+    )
+    doc.add_paragraph(
+        f"Indeks Dasar (Tanpa Penyesuaian): {k['dasar_all']:.2f} "
+        f"(rata-rata 3 jenis; tetap ÷3)"
+    )
 
+    # =========================
+    # Ringkasan (Jenis + Keseluruhan)
+    # =========================
     doc.add_heading("Ringkasan (Jenis + Keseluruhan)", level=2)
-    show = summary_jenis.copy()
-    preferred = [
-        "Jenis","Jumlah_Wilayah","Total_Perpus",
-        "Pop_Total_Jenis","Target68_Total_Jenis","Terkumpul_Jenis","Coverage_Target68_Jenis_%",
-        "Indeks_Dasar_0_100","Indeks_Final_Disesuaikan_0_100","Penyesuaian_Poin"
-    ]
-    show = show[[c for c in preferred if c in show.columns]]
 
-    table = doc.add_table(rows=1, cols=len(show.columns))
-    hdr = table.rows[0].cells
-    for i, c in enumerate(show.columns):
-        hdr[i].text = str(c)
+    if summary_jenis is not None and not summary_jenis.empty:
+        show = summary_jenis.copy()
+
+        preferred = [
+            "Jenis",
+            "Jumlah_Wilayah",
+            "Total_Perpus",
+            "Pop_Total_Jenis",
+            "Target68_Total_Jenis",
+            "Terkumpul_Jenis",
+            "Coverage_Target68_Jenis_%",
+            "Indeks_Dasar_0_100",
+            "Indeks_Final_Disesuaikan_0_100",
+            "Penyesuaian_Poin",
+        ]
+        cols = [c for c in preferred if c in show.columns]
+        show = show[cols].copy()
 
-    for _, row in show.iterrows():
-        cells = table.add_row().cells
+        table = doc.add_table(rows=1, cols=len(show.columns))
+        hdr = table.rows[0].cells
         for i, c in enumerate(show.columns):
-            v = row[c]
-            if pd.isna(v):
-                cells[i].text = ""
-            elif isinstance(v, (float, np.floating)):
-                if c.endswith("_%"):
-                    cells[i].text = f"{float(v):.2f}"
+            hdr[i].text = str(c)
+
+        for _, row in show.iterrows():
+            cells = table.add_row().cells
+            for i, c in enumerate(show.columns):
+                v = row[c]
+                if pd.isna(v):
+                    cells[i].text = ""
+                elif isinstance(v, (float, np.floating)):
+                    if "Coverage" in c:
+                        cells[i].text = f"{float(v):.2f}"
+                    elif "Indeks" in c or "Penyesuaian" in c:
+                        cells[i].text = f"{float(v):.2f}"
+                    else:
+                        cells[i].text = f"{float(v):.0f}"
+                elif isinstance(v, (int, np.integer)):
+                    cells[i].text = str(int(v))
                 else:
-                    cells[i].text = f"{float(v):.2f}"
-            elif isinstance(v, (int, np.integer)):
-                cells[i].text = str(int(v))
-            else:
-                cells[i].text = str(v)
+                    cells[i].text = str(v)
 
-    doc.add_heading("Agregat Wilayah (Keseluruhan)", level=2)
-    if agg_total is not None and not agg_total.empty:
-        cols = [c for c in agg_total.columns if c not in ["group_key"]]
-        t2 = doc.add_table(rows=1, cols=len(cols))
-        h2 = t2.rows[0].cells
-        for i, c in enumerate(cols):
-            h2[i].text = str(c)
-
-        for _, r in agg_total.head(50).iterrows():
-            rr = t2.add_row().cells
-            for i, c in enumerate(cols):
-                vv = r[c]
-                if pd.isna(vv):
-                    rr[i].text = ""
-                elif isinstance(vv, (float, np.floating)):
-                    rr[i].text = f"{float(vv):.2f}"
-                elif isinstance(vv, (int, np.integer)):
-                    rr[i].text = str(int(vv))
-                else:
-                    rr[i].text = str(vv)
+    # =========================
+    # Analisis Naratif (LLM)
+    # =========================
+    doc.add_heading("Analisis Naratif", level=2)
 
-    doc.add_heading("Analisis Naratif (LLM)", level=2)
-    for p in (analysis_text or "").split("\n"):
-        if p.strip():
-            doc.add_paragraph(p.strip())
+    if analysis_text:
+        for p in str(analysis_text).split("\n"):
+            if p.strip():
+                doc.add_paragraph(p.strip())
+    else:
+        doc.add_paragraph("Analisis tidak tersedia.")
 
     outpath = tempfile.mktemp(suffix=".docx")
     doc.save(outpath)
     return outpath
 
-
 # ============================================================
 # 15) CORE RUN
 # ============================================================