ai insight rework #3, add root cause to daily ai insight

backend/apps/operations/services/cp707_knowledge.py

@@ -492,7 +492,7 @@ def analyze_mortality(mortality_rate_pct: Any, day_age: Any) -> dict[str, Any]:
         dilarang = ["rendah", "normal", "baik", "aman", "terkendali", "sedikit"]
         message = (
             f"Mortalitas kumulatif {rate:.2f}% adalah SANGAT TINGGI — melebihi batas kritis "
-            f"CP 707 (>7%). Lakukan nekropsi darurat dan perketat biosekuriti."
+            f"CP 707 (>7%)."
         )
     elif rate >= MORTALITY_THRESHOLDS["warning_pct"]:
         status = "warning"

backend/apps/operations/services/insight_service.py

@@ -32,6 +32,21 @@ _INFERENCE_LOCK = threading.Lock()
 
 _NUMERIC_PIPE_ROW = re.compile(r"^[\d.,]+(\s*\|\s*[\d.,]*)+$")
 
+DAILY_JSON_MARKER = "<!--daily_json-->"
+
+
+def parse_embedded_daily(text: str) -> dict[str, Any] | None:
+    """Extract structured daily payload (akar_masalah, insight) from stored insight_text."""
+    if not text or DAILY_JSON_MARKER not in text:
+        return None
+    raw = text.split(DAILY_JSON_MARKER, 1)[1].strip()
+    try:
+        data = json.loads(raw)
+    except json.JSONDecodeError:
+        return None
+    return data if isinstance(data, dict) else None
+
+
 # Stored in AIInsight.alert — condition of graded data, not narrative text.
 ALERT_HEALTHY = "healthy"
 ALERT_WARNING = "warning"
@@ -122,7 +137,7 @@ ATURAN STANDAR CP 707 — DILARANG MENGARANG (WAJIB DIPATUHI):
 - Bobot standar hanya hari 1–37. Di luar itu "tidak tercantum di buku".
 
 FORMAT OUTPUT (JSON SAJA):
-{"kesimpulan":"...","insight":"..."}
+{"kesimpulan":"...","akar_masalah":"...","insight":"..."}
 """
 
 END_CYCLE_OUTPUT_RULES = """
@@ -241,6 +256,7 @@ def build_insight_user_prompt(
                 lines.append(f"  - {b}")
 
     # 5. Length contract + field role contract
+    actual_alert = alert_from_graded(graded) if graded else ALERT_UNKNOWN
     if is_end_cycle:
         lines.append(
             "\nPANJANG WAJIB: kesimpulan = 1-3 kalimat PENILAIAN DATA SAJA (tanpa sebab/aksi). "
@@ -252,13 +268,32 @@ def build_insight_user_prompt(
             "konsultasikan) di kesimpulan — insight HARUS mengandung minimal satu kata aksi."
         )
     else:
-        lines.append(
-            "\nPANJANG WAJIB: insight = narasi 3-6 kalimat berurutan: "
-            "(1) angka aktual vs standar CP 707, (2) penyebab/implikasi, "
-            "(3) tindakan konkret. kesimpulan = 1-3 kalimat PENILAIAN DATA SAJA (tanpa sebab/aksi). "
-            "Satu kalimat singkat = gagal. DILARANG menulis kata aksi (lakukan, periksa, sebaiknya, "
-            "konsultasikan) di kesimpulan — insight HARUS mengandung minimal satu kata aksi."
-        )
+        if actual_alert in (ALERT_WARNING, ALERT_CRITICAL):
+            lines.append(
+                f"\nPANJANG WAJIB (STATUS AKTUAL ADALAH {actual_alert.upper()} — ADA ANOMALI/MASALAH): "
+                "kesimpulan = 1-3 kalimat PENILAIAN DATA SAJA (tanpa sebab/aksi, sebutkan angka aktual vs standar CP 707). "
+                "akar_masalah = 1-3 kalimat ANALISIS AKAR PENYEBAB & FAKTOR PEMICU DEVIASI (soroti anomali mortalitas, fluktuasi konsumsi pakan, atau deviasi mikroklimat suhu/kelembapan). DILARANG KERAS menulis 'kondisi optimal' atau 'tidak terdeteksi anomali' karena status data sedang bermasalah. "
+                "insight = narasi 3-5 kalimat REKOMENDASI TINDAKAN KONKRET & PANDUAN SOP CP 707. "
+                "Satu kalimat singkat = gagal. DILARANG menulis kata aksi (lakukan, periksa, sebaiknya, "
+                "konsultasikan) di kesimpulan — insight HARUS mengandung minimal satu kata aksi."
+            )
+        elif actual_alert == ALERT_HEALTHY:
+            lines.append(
+                f"\nPANJANG WAJIB (STATUS AKTUAL ADALAH {actual_alert.upper()} — KONDISI OPTIMAL/NORMAL): "
+                "kesimpulan = 1-3 kalimat PENILAIAN DATA SAJA (konfirmasi performa sesuai standar CP 707, tanpa sebab/aksi). "
+                "akar_masalah = 1-2 kalimat konfirmasi bahwa parameter lingkungan dan pakan terkendali dengan baik tanpa indikasi deviasi. "
+                "insight = narasi 3-5 kalimat panduan mempertahankan SOP CP 707 dan monitoring rutin. "
+                "Satu kalimat singkat = gagal. DILARANG menulis kata aksi (lakukan, periksa, sebaiknya, "
+                "konsultasikan) di kesimpulan — insight HARUS mengandung minimal satu kata aksi."
+            )
+        else:
+            lines.append(
+                "\nPANJANG WAJIB: kesimpulan = 1-3 kalimat PENILAIAN DATA SAJA (tanpa sebab/aksi). "
+                "akar_masalah = 1-3 kalimat ANALISIS AKAR PENYEBAB / FAKTOR PEMICU berdasarkan data yang tersedia. "
+                "insight = narasi 3-5 kalimat REKOMENDASI TINDAKAN KONKRET & PANDUAN SOP CP 707. "
+                "Satu kalimat singkat = gagal. DILARANG menulis kata aksi (lakukan, periksa, sebaiknya, "
+                "konsultasikan) di kesimpulan — insight HARUS mengandung minimal satu kata aksi."
+            )
 
     # 6. Output schema
     if is_end_cycle:
@@ -272,12 +307,30 @@ def build_insight_user_prompt(
             ' - JANGAN salin teks <> dari contoh; tulis kalimat lengkap sendiri.'
         )
     else:
-        lines.append(
-            '\nBALAS HANYA JSON persis: '
-            '{"kesimpulan":"<ringkasan penilaian 1-3 kalimat>",'
-            '"insight":"<narasi panjang 3-6 kalimat: aktual vs standar, penyebab, tindakan>"}'
-            ' - JANGAN salin teks <> dari contoh; tulis kalimat lengkap sendiri.'
-        )
+        if actual_alert in (ALERT_WARNING, ALERT_CRITICAL):
+            lines.append(
+                '\nBALAS HANYA JSON persis: '
+                '{"kesimpulan":"<ringkasan penilaian data aktual vs standar 1-3 kalimat>",'
+                '"akar_masalah":"<analisis faktor pemicu / akar masalah deviasi dari data faktual>",'
+                '"insight":"<narasi rekomendasi 3-5 kalimat: tindakan konkret & panduan SOP CP 707>"}'
+                ' - JANGAN salin teks <> dari contoh; tulis kalimat lengkap sendiri.'
+            )
+        elif actual_alert == ALERT_HEALTHY:
+            lines.append(
+                '\nBALAS HANYA JSON persis: '
+                '{"kesimpulan":"<ringkasan penilaian data sesuai standar CP 707 1-3 kalimat>",'
+                '"akar_masalah":"<konfirmasi parameter operasional terkendali baik tanpa anomali>",'
+                '"insight":"<narasi rekomendasi 3-5 kalimat: panduan SOP CP 707 & monitoring berkala>"}'
+                ' - JANGAN salin teks <> dari contoh; tulis kalimat lengkap sendiri.'
+            )
+        else:
+            lines.append(
+                '\nBALAS HANYA JSON persis: '
+                '{"kesimpulan":"<ringkasan penilaian data 1-3 kalimat>",'
+                '"akar_masalah":"<analisis faktor pemicu berdasarkan data yang ada>",'
+                '"insight":"<narasi rekomendasi 3-5 kalimat: tindakan konkret & panduan SOP CP 707>"}'
+                ' - JANGAN salin teks <> dari contoh; tulis kalimat lengkap sendiri.'
+            )
 
     return "\n".join(lines)
 
@@ -671,16 +724,27 @@ def parse_llm_json(text: str) -> dict[str, str] | None:
         or parsed.get("summary")
         or ""
     )
+    akar_masalah = (
+        parsed.get("akar_masalah")
+        or parsed.get("root_cause")
+        or parsed.get("akar_penyebab")
+        or parsed.get("penyebab")
+        or parsed.get("faktor_penyebab")
+        or parsed.get("faktor_pemicu")
+        or ""
+    )
     insight = (
         parsed.get("insight")
         or parsed.get("rekomendasi")
         or parsed.get("insights")
+        or parsed.get("saran")
         or ""
     )
-    if not kesimpulan and not insight:
+    if not kesimpulan and not insight and not akar_masalah:
         return None
     return {
         "kesimpulan": str(kesimpulan) or "Model tidak mengembalikan kesimpulan eksplisit.",
+        "akar_masalah": str(akar_masalah).strip() if akar_masalah else "",
         "insight": str(insight) or "Model tidak mengembalikan rekomendasi eksplisit.",
     }
 
@@ -737,11 +801,17 @@ def _text_soft_labels_mortality(text: str) -> bool:
     return bool(_SOFT_MORTALITY_WORD.search(text) and _MENTIONS_MORTALITY.search(text))
 
 
+_OPTIMAL_CONTRADICTION = re.compile(
+    r"\b(kondisi\s+operasional\s+optimal|tidak\s+terdeteksi\s+(?:indikasi\s+)?anomali|semua\s+parameter\s+normal|kondisi\s+optimal|operasional\s+optimal|tidak\s+ada\s+anomali)\b",
+    re.IGNORECASE,
+)
+
+
 def enforce_mortality_wording(
     parsed: dict[str, Any],
     graded: dict[str, Any] | None,
 ) -> dict[str, Any]:
-    """Rewrite LLM text that calls high mortality 'rendah/normal' (small-model slip)."""
+    """Rewrite LLM text that calls high mortality 'rendah/normal' or claims optimal when critical."""
     mort = ((graded or {}).get("analyses") or {}).get("mortality") or {}
     status = str(mort.get("status") or "").lower()
     if status not in ("warning", "critical"):
@@ -754,23 +824,33 @@ def enforce_mortality_wording(
 
     out = dict(parsed)
     kesimpulan = str(out.get("kesimpulan") or "")
+    akar_masalah = str(out.get("akar_masalah") or "")
     insight = str(out.get("insight") or "")
 
-    if not (_text_soft_labels_mortality(kesimpulan) or _text_soft_labels_mortality(insight)):
+    has_soft_kesimpulan = _text_soft_labels_mortality(kesimpulan)
+    has_soft_akar = _text_soft_labels_mortality(akar_masalah) or bool(_OPTIMAL_CONTRADICTION.search(akar_masalah))
+    has_soft_insight = _text_soft_labels_mortality(insight)
+
+    if not (has_soft_kesimpulan or has_soft_akar or has_soft_insight):
         return out
 
-    # Prefer the deterministic graded message; keep non-mortality insight if clean.
-    if message:
-        out["kesimpulan"] = message
-    else:
-        pct_part = f" ({pct})" if pct else ""
-        out["kesimpulan"] = (
-            f"Mortalitas kumulatif{pct_part} adalah {label} menurut ambang CP 707."
+    pct_part = f" ({pct})" if pct else ""
+    if has_soft_kesimpulan:
+        if message:
+            out["kesimpulan"] = message
+        else:
+            out["kesimpulan"] = (
+                f"Mortalitas kumulatif{pct_part} adalah {label} menurut ambang CP 707."
+            )
+
+    if has_soft_akar:
+        out["akar_masalah"] = (
+            f"Lonjakan mortalitas kumulatif{pct_part} yang tergolong {label} menjadi pemicu deviasi performa, mengindikasikan adanya stres lingkungan, tantangan biosekuriti, atau paparan patogen."
         )
 
-    if _text_soft_labels_mortality(insight):
+    if has_soft_insight:
         out["insight"] = (
-            "Segera tinjau penyebab kematian (nekropsi bila kritis), perketat biosekuriti, "
+            "Segera lakukan nekropsi pada ayam mati untuk identifikasi patogen, perketat biosekuriti kandang, "
             "dan pantau mortalitas harian hingga tren menurun."
         )
     return out
@@ -792,6 +872,7 @@ def enforce_bw_wording(
 
     out = dict(parsed)
     kesimpulan = str(out.get("kesimpulan") or "")
+    akar_masalah = str(out.get("akar_masalah") or "")
 
     # If graded status is OK, but summary claims it is below standard / critical:
     if status == "ok" and any(
@@ -803,6 +884,14 @@ def enforce_bw_wording(
         elif actual is not None and std is not None:
             out["kesimpulan"] = f"Bobot badan ayam ({actual:g}g) sesuai dengan target standar ({std:g}g)."
 
+    # If graded status is warning/critical for BW, but akar_masalah claims optimal:
+    if status in ("warning", "critical") and _OPTIMAL_CONTRADICTION.search(akar_masalah):
+        diff_str = f" ({actual:g}g vs {std:g}g)" if actual is not None and std is not None else ""
+        out["akar_masalah"] = (
+            f"Pertumbuhan bobot badan tertinggal dari target standar CP 707{diff_str}, "
+            "dipicu oleh fluktuasi asupan pakan harian atau ketidaksesuaian mikroklimat kandang."
+        )
+
     return out
 
 
@@ -824,7 +913,7 @@ def _placeholder_text(value: str) -> bool:
 def sanitize_insight_narrative(parsed: dict[str, Any]) -> dict[str, Any]:
     """Deterministic cleanup of narrative fields after the LLM."""
     out = dict(parsed)
-    for key in ("kesimpulan", "insight", "summary", "insight_text"):
+    for key in ("kesimpulan", "akar_masalah", "insight", "summary", "insight_text"):
         if key in out and out[key] is not None:
             out[key] = collapse_duplicate_kandang(str(out[key]))
     return out
@@ -912,15 +1001,36 @@ def decode_citations(raw: Any) -> list[dict[str, Any]]:
 def serialize_insight(row: AIInsight) -> dict[str, Any]:
     norm_citations = decode_citations(row.citations)
     summary = collapse_duplicate_kandang(row.summary or "")
-    insight_body = collapse_duplicate_kandang(row.insight_text or "")
-    insight_text = "\n\n".join(
-        part for part in [summary, insight_body] if part
-    ) or insight_body or ""
-    structured = root_cause.parse_embedded_end_cycle(insight_body)
+    insight_raw = collapse_duplicate_kandang(row.insight_text or "")
+
+    structured = root_cause.parse_embedded_end_cycle(insight_raw)
     if structured and summary and not structured.get("kesimpulan"):
         structured = {**structured, "kesimpulan": summary}
     elif structured:
         structured = sanitize_insight_narrative(structured)
+
+    embedded_daily = parse_embedded_daily(insight_raw)
+    akar_masalah = ""
+    if embedded_daily:
+        akar_masalah = str(embedded_daily.get("akar_masalah") or "").strip()
+        insight_body = str(
+            embedded_daily.get("insight") or insight_raw.split(DAILY_JSON_MARKER, 1)[0]
+        ).strip()
+    elif structured:
+        insight_body = insight_raw.split(root_cause.END_CYCLE_JSON_MARKER, 1)[0].strip()
+    else:
+        insight_body = insight_raw
+
+    insight_body = collapse_duplicate_kandang(insight_body)
+    akar_masalah = collapse_duplicate_kandang(akar_masalah)
+
+    parts = [summary]
+    if akar_masalah:
+        parts.append(akar_masalah)
+    if insight_body:
+        parts.append(insight_body)
+    insight_text = "\n\n".join(part for part in parts if part) or insight_body or ""
+
     return {
         "success": True,
         "id": row.pk,
@@ -930,6 +1040,7 @@ def serialize_insight(row: AIInsight) -> dict[str, Any]:
         "report_type": row.report_type,
         "report_period": row.report_period,
         "summary": summary,
+        "akar_masalah": akar_masalah,
         "insight": insight_body,
         "insight_text": insight_text,
         "structured_end_cycle": structured,
@@ -1176,10 +1287,17 @@ def generate_insight(
             parsed = enforce_mortality_wording(parsed, graded)
             parsed = enforce_bw_wording(parsed, graded)
             parsed = sanitize_insight_narrative(parsed)
-            insight_text = parsed["insight"]
             summary = parsed["kesimpulan"]
-        if _placeholder_text(summary) or _placeholder_text(insight_text):
-            degenerate_reason = f"kesimpulan={summary!r} insight={insight_text!r}"
+            akar_masalah = parsed.get("akar_masalah", "").strip()
+            clean_insight = parsed["insight"]
+            if akar_masalah:
+                daily_payload = {"akar_masalah": akar_masalah, "insight": clean_insight}
+                insight_text = f"{clean_insight}\n\n{DAILY_JSON_MARKER}\n{json.dumps(daily_payload, ensure_ascii=False)}"
+            else:
+                insight_text = clean_insight
+        check_insight = clean_insight if not is_end_cycle else insight_text
+        if _placeholder_text(summary) or _placeholder_text(check_insight):
+            degenerate_reason = f"kesimpulan={summary!r} insight={check_insight!r}"
             user_prompt += (
                 "\nCATATAN: keluaran sebelumnya hanya placeholder. "
                 "Tulis kalimat lengkap sendiri untuk kesimpulan dan insight."

backend/apps/operations/tests_insight_quality.py

@@ -672,6 +672,88 @@ class RootCauseTests(TestCase):
         self.assertEqual(sanitized["perbaikan_siklus_berikutnya"][0]["id"], "pakan_akses")
 
 
+class DailyAkarMasalahTests(TestCase):
+    """Test daily AI insight 3-section format (kesimpulan, akar_masalah, insight)."""
+
+    def test_parse_llm_json_with_akar_masalah(self):
+        payload = json.dumps({
+            "kesimpulan": "FCR 1.40 pada hari ke-28 berada di atas standar CP 707 (1.315).",
+            "akar_masalah": "Fluktuasi suhu kandang malam hari dan akses pakan tidak merata.",
+            "insight": "Lakukan kalibrasi pemanas dan ratakan distribusi pakan di sepanjang brooding area."
+        })
+        parsed = insight_service.parse_llm_json(payload)
+        self.assertIsNotNone(parsed)
+        self.assertEqual(parsed["kesimpulan"], "FCR 1.40 pada hari ke-28 berada di atas standar CP 707 (1.315).")
+        self.assertEqual(parsed["akar_masalah"], "Fluktuasi suhu kandang malam hari dan akses pakan tidak merata.")
+        self.assertIn("kalibrasi pemanas", parsed["insight"])
+
+    def test_parse_llm_json_variants(self):
+        payload = json.dumps({
+            "summary": "Kondisi pakan normal.",
+            "root_cause": "Kondisi operasional optimal, tidak terdeteksi indikasi deviasi.",
+            "rekomendasi": "Pertahankan SOP saat ini."
+        })
+        parsed = insight_service.parse_llm_json(payload)
+        self.assertIsNotNone(parsed)
+        self.assertEqual(parsed["kesimpulan"], "Kondisi pakan normal.")
+        self.assertEqual(parsed["akar_masalah"], "Kondisi operasional optimal, tidak terdeteksi indikasi deviasi.")
+        self.assertEqual(parsed["insight"], "Pertahankan SOP saat ini.")
+
+    def test_parse_llm_json_legacy_fallback(self):
+        payload = json.dumps({
+            "kesimpulan": "Data normal.",
+            "insight": "Lanjutkan pemantauan harian."
+        })
+        parsed = insight_service.parse_llm_json(payload)
+        self.assertIsNotNone(parsed)
+        self.assertEqual(parsed["kesimpulan"], "Data normal.")
+        self.assertEqual(parsed["akar_masalah"], "")
+        self.assertEqual(parsed["insight"], "Lanjutkan pemantauan harian.")
+
+    def test_embedded_daily_serialization(self):
+        clean_insight = "Lakukan penyesuaian tirai kandang dan ventilasi minimal."
+        akar_masalah = "Suhu brooding terlalu dingin di malam hari (26C vs 32C)."
+        daily_json = json.dumps({"akar_masalah": akar_masalah, "insight": clean_insight}, ensure_ascii=False)
+        stored_text = f"{clean_insight}\n\n{insight_service.DAILY_JSON_MARKER}\n{daily_json}"
+
+        mock_row = MagicMock()
+        mock_row.pk = 1
+        mock_row.cycle_id = 10
+        mock_row.kandang_id = 2
+        mock_row.topic = "fcr"
+        mock_row.report_type = "page"
+        mock_row.report_period = "current"
+        mock_row.summary = "FCR tinggi pada hari ke-7."
+        mock_row.insight_text = stored_text
+        mock_row.alert = "warning"
+        mock_row.citations = "[]"
+        mock_row.date = None
+        mock_row.created_at = None
+        mock_row.updated_at = None
+
+        serialized = insight_service.serialize_insight(mock_row)
+        self.assertTrue(serialized["success"])
+        self.assertEqual(serialized["summary"], "FCR tinggi pada hari ke-7.")
+        self.assertEqual(serialized["akar_masalah"], akar_masalah)
+        self.assertEqual(serialized["insight"], clean_insight)
+        self.assertIn(akar_masalah, serialized["insight_text"])
+        self.assertIn(clean_insight, serialized["insight_text"])
+
+    def test_daily_prompt_structure(self):
+        prompt = insight_service.build_insight_user_prompt(
+            topic="fcr",
+            kandang_name="Kandang 01",
+            report_type="page",
+            report_period="current",
+            context={"fcr_terakhir": 1.4},
+            graded={"analyses": {"fcr": {"status": "warning", "message": "FCR tinggi"}}},
+            is_end_cycle=False,
+        )
+        self.assertIn("akar_masalah", prompt)
+        self.assertIn("ANALISIS AKAR PENYEBAB", prompt)
+        self.assertIn('"akar_masalah":"<analisis faktor pemicu', prompt)
+
+
 class TraceLintTests(TestCase):
     """Test rag_trace.jsonl linting logic."""
 

components/AiInsightCard.tsx

@@ -1,5 +1,5 @@
 /**
- * Dashboard AI Insight card (page / daily / weekly / end_cycle report modes).
+ * Dashboard AI Insight card (daily / end_cycle report modes).
  *
  * Parallel client to `PageAiInsight` (topic pages) — same API, different UX.
  * Architecture: docs/ai-insight/README.md
@@ -23,6 +23,7 @@ import {
   scopeDashboardInsightMetrics,
 } from '../utils/insightContextBuilders.ts';
 import { getCobbStandardForDay } from '../utils/insightHelpers.ts';
+import { parseAiResult, type AiResult } from '../utils/insightParse.ts';
 import { formatRatio } from '../utils/format.ts';
 import {
   HeroFigure,
@@ -253,6 +254,7 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
   const { selectedCycle, selectedKandang, selectedSite, selectedKandangId } = useFarm();
 
   const [insightText, setInsightText] = useState('');
+  const [dailyInsight, setDailyInsight] = useState<AiResult | null>(null);
   const [structuredInsight, setStructuredInsight] = useState<InsightStructuredReport | null>(null);
   const [endCycleInsight, setEndCycleInsight] = useState<EndCycleStructuredInsight | null>(null);
   const [citations, setCitations] = useState<InsightCitation[]>([]);
@@ -275,9 +277,7 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
     reportType === 'daily'
       ? (dayPeriod ??
         (typeof currentDayVal === 'number' && currentDayVal >= 0 ? `Hari ${currentDayVal}` : null))
-      : reportType === 'weekly'
-        ? dayPeriod
-        : null;
+      : null;
 
   const scopedMetrics = useMemo(() => {
     if (!dashboardMetrics) return null;
@@ -293,7 +293,9 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
       text: string,
       nextCitations?: InsightCitation[] | 'cache' | 'local_fallback',
       structuredEndCycle?: EndCycleStructuredInsight | null,
-      summary?: string | null
+      summary?: string | null,
+      akarMasalah?: string | null,
+      insightBody?: string | null
     ) => {
       const citationsArg = Array.isArray(nextCitations) ? nextCitations : [];
       setInsightText(text);
@@ -305,6 +307,22 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
       // Prefer end-cycle structured UI over legacy multi-topic structured dump.
       setStructuredInsight(endCycle ? null : normalizeStructuredInsight(text));
       setCitations(citationsArg);
+
+      if (!endCycle) {
+        if (summary || akarMasalah || insightBody) {
+          setDailyInsight({
+            summary: summary || '',
+            akar_masalah: akarMasalah || undefined,
+            insight: insightBody || text || '',
+          });
+        } else if (text) {
+          setDailyInsight(parseAiResult(text));
+        } else {
+          setDailyInsight(null);
+        }
+      } else {
+        setDailyInsight(null);
+      }
     },
     []
   );
@@ -451,7 +469,9 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
           apiResult.insight_text,
           apiResult.citations,
           apiResult.structured_end_cycle ?? null,
-          apiResult.summary
+          apiResult.summary,
+          apiResult.akar_masalah,
+          apiResult.insight
         );
         setLastUpdated(new Date());
         setDetailsOpen(false);
@@ -1013,11 +1033,45 @@ export const AiInsightCard: React.FC<AiInsightCardProps> = ({
                 </>
               )}
             </div>
+          ) : dailyInsight ? (
+            <div className="space-y-4">
+              <div className="rounded-xl border border-gray-100 bg-white p-5 shadow-sm">
+                <h4 className="text-sm font-bold text-gray-800 mb-2 flex items-center gap-2">
+                  <i className="fa-solid fa-circle-check text-green-600" /> Kesimpulan
+                </h4>
+                <p className="text-sm text-gray-700 bg-gray-50 p-3 rounded-lg border border-gray-100">
+                  {dailyInsight.summary}
+                </p>
+              </div>
+
+              {dailyInsight.akar_masalah && (
+                <div className="rounded-xl border border-amber-100/80 bg-amber-50/40 p-5 shadow-sm">
+                  <h4 className="text-sm font-bold text-gray-800 mb-2 flex items-center gap-2">
+                    <i className="fa-solid fa-magnifying-glass-chart text-amber-600" /> Akar Masalah
+                  </h4>
+                  <p className="text-sm text-gray-700 bg-white/80 p-3 rounded-lg border border-amber-100/80">
+                    {dailyInsight.akar_masalah}
+                  </p>
+                </div>
+              )}
+
+              <div className="rounded-xl border border-gray-100 bg-white p-5 shadow-sm">
+                <h4 className="text-sm font-bold text-gray-800 mb-2 flex items-center gap-2">
+                  <i className="fa-solid fa-brain text-red-600" /> AI Insight & Rekomendasi
+                </h4>
+                <p className="text-sm text-gray-700 bg-gray-50 p-3 rounded-lg border border-gray-100 whitespace-pre-wrap">
+                  {dailyInsight.insight}
+                </p>
+                <CitationsBlock citations={citations} />
+              </div>
+            </div>
           ) : insightText ? (
             <div className="text-sm text-gray-800 leading-relaxed whitespace-pre-wrap">
               {insightText.includes(END_CYCLE_JSON_MARKER)
                 ? insightText.split(END_CYCLE_JSON_MARKER)[0]?.trim()
-                : insightText}
+                : insightText.includes('<!--daily_json-->')
+                  ? insightText.split('<!--daily_json-->')[0]?.trim()
+                  : insightText}
               <CitationsBlock citations={citations} />
             </div>
           ) : (

components/shared/PageAiInsight.tsx

@@ -603,10 +603,11 @@ export const PageAiInsight: React.FC<PageAiInsightProps> = ({
         }
 
         const text = apiResult.insight_text ?? '';
-        let parsed: { summary: string; insight: string } | null = null;
-        if (apiResult.summary || apiResult.insight) {
+        let parsed: AiResult | null = null;
+        if (apiResult.summary || apiResult.insight || apiResult.akar_masalah) {
           parsed = {
             summary: apiResult.summary || '',
+            akar_masalah: apiResult.akar_masalah || undefined,
             insight: apiResult.insight || apiResult.insight_text || '',
           };
         } else {
@@ -619,6 +620,7 @@ export const PageAiInsight: React.FC<PageAiInsightProps> = ({
 
         const wrapped: PageInsightResult = {
           summary: parsed.summary,
+          akar_masalah: parsed.akar_masalah,
           insight: parsed.insight,
           citations: apiResult.citations,
         };
@@ -1041,9 +1043,20 @@ export const PageAiInsight: React.FC<PageAiInsightProps> = ({
                 </p>
               </div>
 
+              {result.akar_masalah && (
+                <div className="mt-4">
+                  <h4 className="text-sm font-bold text-gray-800 mb-2 flex items-center gap-2">
+                    <i className="fa-solid fa-magnifying-glass-chart text-amber-600" /> Akar Masalah
+                  </h4>
+                  <p className="text-sm text-gray-700 bg-amber-50/50 p-3 rounded-lg border border-amber-100/80">
+                    {result.akar_masalah}
+                  </p>
+                </div>
+              )}
+
               <div className="mt-4">
                 <h4 className="text-sm font-bold text-gray-800 mb-2 flex items-center gap-2">
-                  <i className="fa-solid fa-brain text-red-600" /> AI Insight
+                  <i className="fa-solid fa-brain text-red-600" /> AI Insight & Rekomendasi
                 </h4>
                 <p className="text-sm text-gray-700 bg-gray-50 p-3 rounded-lg border border-gray-100 whitespace-pre-wrap">
                   {result.insight}

types/api.ts

@@ -337,6 +337,7 @@ export type InsightApiResponse = {
   success?: boolean;
   insight_text: string;
   summary?: string;
+  akar_masalah?: string;
   insight?: string;
   structured?: InsightStructuredReport | null;
   structured_end_cycle?: EndCycleStructuredInsight | null;

utils/__tests__/insightParse.test.ts

@@ -0,0 +1,53 @@
+import { describe, expect, it } from 'vitest';
+import { parseAiResult } from '../insightParse.ts';
+
+describe('parseAiResult with akar_masalah', () => {
+  it('parses standard 3-section json output', () => {
+    const raw = JSON.stringify({
+      kesimpulan: 'FCR 1.40 pada hari ke-28 berada di atas standar CP 707 (1.315).',
+      akar_masalah: 'Suhu lingkungan fluktuatif dan distribusi pakan kurang merata.',
+      insight: 'Lakukan kalibrasi suhu pemanas dan ratakan tempat pakan.',
+    });
+    const res = parseAiResult(raw);
+    expect(res).not.toBeNull();
+    expect(res?.summary).toBe('FCR 1.40 pada hari ke-28 berada di atas standar CP 707 (1.315).');
+    expect(res?.akar_masalah).toBe(
+      'Suhu lingkungan fluktuatif dan distribusi pakan kurang merata.'
+    );
+    expect(res?.insight).toBe('Lakukan kalibrasi suhu pemanas dan ratakan tempat pakan.');
+  });
+
+  it('handles markdown fences and think tags', () => {
+    const raw = `
+<think>
+Evaluating data for day 28. FCR is high.
+</think>
+\`\`\`json
+{
+  "summary": "Kondisi pakan stabil.",
+  "root_cause": "Kondisi operasional optimal, tidak terdeteksi indikasi anomali.",
+  "rekomendasi": "Pertahankan ventilasi dan jadwal pemberian pakan."
+}
+\`\`\`
+`;
+    const res = parseAiResult(raw);
+    expect(res).not.toBeNull();
+    expect(res?.summary).toBe('Kondisi pakan stabil.');
+    expect(res?.akar_masalah).toBe(
+      'Kondisi operasional optimal, tidak terdeteksi indikasi anomali.'
+    );
+    expect(res?.insight).toBe('Pertahankan ventilasi dan jadwal pemberian pakan.');
+  });
+
+  it('tolerates legacy 2-field format without akar_masalah', () => {
+    const raw = JSON.stringify({
+      kesimpulan: 'Bobot badan sesuai target.',
+      insight: 'Lanjutkan monitoring bobot mingguan.',
+    });
+    const res = parseAiResult(raw);
+    expect(res).not.toBeNull();
+    expect(res?.summary).toBe('Bobot badan sesuai target.');
+    expect(res?.akar_masalah).toBeUndefined();
+    expect(res?.insight).toBe('Lanjutkan monitoring bobot mingguan.');
+  });
+});

utils/insightParse.ts

@@ -15,6 +15,7 @@
 
 export interface AiResult {
   summary: string;
+  akar_masalah?: string;
   insight: string;
 }
 
@@ -28,6 +29,17 @@ const KESIMPULAN_KEYS = [
   'conclusion',
 ];
 
+/** Field names seen standing in for the root cause / factors. */
+const AKAR_MASALAH_KEYS = [
+  'akar_masalah',
+  'akar_penyebab',
+  'root_cause',
+  'penyebab',
+  'faktor_penyebab',
+  'faktor_pemicu',
+  'indikasi_masalah',
+];
+
 /** Field names seen standing in for the recommendation. */
 const INSIGHT_KEYS = [
   'insight',
@@ -122,6 +134,9 @@ export const parseAiResult = (text: string): AiResult | null => {
   const kesimpulanHit = takeFirst(parsed, KESIMPULAN_KEYS);
   if (kesimpulanHit) used.add(kesimpulanHit.key);
 
+  const akarMasalahHit = takeFirst(parsed, AKAR_MASALAH_KEYS);
+  if (akarMasalahHit) used.add(akarMasalahHit.key);
+
   const insightHit = takeFirst(parsed, INSIGHT_KEYS);
   if (insightHit) used.add(insightHit.key);
 
@@ -136,6 +151,7 @@ export const parseAiResult = (text: string): AiResult | null => {
     .filter((line) => line.length > 0);
 
   let kesimpulan = kesimpulanHit?.text ?? '';
+  const akarMasalah = akarMasalahHit?.text ?? '';
   let insight = insightHit?.text ?? '';
 
   if (!kesimpulan && leftovers.length > 0) {
@@ -147,10 +163,11 @@ export const parseAiResult = (text: string): AiResult | null => {
     insight = [insight, ...leftovers].filter(Boolean).join('\n\n');
   }
 
-  if (!kesimpulan && !insight) return null;
+  if (!kesimpulan && !insight && !akarMasalah) return null;
 
   return {
     summary: kesimpulan || 'Model tidak mengembalikan ringkasan eksplisit.',
+    akar_masalah: akarMasalah || undefined,
     insight: insight || 'Model tidak mengembalikan rekomendasi eksplisit.',
   };
 };