feat: add 5 dashboard features — dark mode, trade history, backtests, model insights, alerts
- Dark mode: class-based theme toggle with localStorage persistence and flash prevention - Trade History (/trades): paginated table, stats cards, equity curve chart with DB API endpoints - Backtest Viewer (/backtests): log parser for 35 backtest results, sidebar + detail + comparison tabs - Model Insights: dashboard card + dialog showing feature importance, regime distribution, training history - Alert/Signal Log (/alerts): signal stats, filterable table with execution tracking - API: 8 new endpoints with psycopg2 DB connection pool - Dark mode sweep across books page, about dialog, and all dashboard components - Architecture docs rewritten with Mermaid diagrams (23 docs) - README and FEATURES.md rewritten bilingual (Indonesian + English) - main_live.py: write model_metrics.json on startup and retrain Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
GifariKemal
co-authored by
Claude Opus 4.6
Claude Opus 4.6
parent
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commit
e8355b3f62
@@ -1,4 +1,4 @@
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# Dynamic Confidence — Penyesuaian Threshold Otomatis
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# *Dynamic Confidence* --- Penyesuaian *Threshold* Otomatis
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> **File:** `src/dynamic_confidence.py`
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> **Class:** `DynamicConfidenceManager`
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@@ -6,21 +6,73 @@
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---
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## Apa Itu Dynamic Confidence?
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## Apa Itu *Dynamic Confidence*?
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Dynamic Confidence adalah sistem yang **menyesuaikan confidence threshold ML secara otomatis** berdasarkan kondisi pasar saat ini. Saat kondisi ideal, threshold diturunkan agar lebih banyak peluang. Saat kondisi buruk, threshold dinaikkan untuk lebih selektif.
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*Dynamic Confidence* adalah sistem yang **menyesuaikan confidence *threshold* ML secara otomatis** berdasarkan kondisi pasar saat ini. Saat kondisi ideal, *threshold* diturunkan agar lebih banyak peluang. Saat kondisi buruk, *threshold* dinaikkan untuk lebih selektif.
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**Analogi:** Dynamic Confidence seperti **termometer yang mengatur AC otomatis** — saat cuaca panas (pasar bagus), AC diset dingin (threshold rendah, lebih banyak trade). Saat cuaca dingin (pasar buruk), AC dimatikan (threshold tinggi, kurangi trade).
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**Analogi:** *Dynamic Confidence* seperti **termometer yang mengatur AC otomatis** --- saat cuaca panas (pasar bagus), AC diset dingin (*threshold* rendah, lebih banyak trade). Saat cuaca dingin (pasar buruk), AC dimatikan (*threshold* tinggi, kurangi trade).
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---
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## Flowchart
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```mermaid
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flowchart TD
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A["Kondisi Market Saat Ini"] --> B["6 Faktor Dianalisis"]
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B --> F1["1. Session<br/>+/- 20 poin"]
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B --> F2["2. Regime<br/>+/- 15 poin"]
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B --> F3["3. Volatility<br/>+/- 10 poin"]
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B --> F4["4. Trend Clarity<br/>+/- 10 poin"]
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B --> F5["5. SMC Confluence<br/>+/- 10 poin"]
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B --> F6["6. ML Alignment<br/>+/- 5 poin"]
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F1 --> S["Score (0 - 100)"]
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F2 --> S
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F3 --> S
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F4 --> S
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F5 --> S
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F6 --> S
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S --> Q{"Quality Level?"}
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Q -->|"Score >= 80"| E["EXCELLENT<br/>Threshold: 60%"]
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Q -->|"Score 65-79"| G["GOOD<br/>Threshold: 65%"]
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Q -->|"Score 50-64"| M["MODERATE<br/>Threshold: 70%"]
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Q -->|"Score 35-49"| P["POOR<br/>Threshold: 80%"]
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Q -->|"Score < 35"| AV["AVOID<br/>Threshold: 85%"]
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E --> D{"ML Confidence<br/>>= Threshold?"}
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G --> D
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M --> D
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P --> D
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AV --> SKIP["SKIP --- Jangan Trade"]
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D -->|"YES"| ENTRY["ENTRY Diizinkan"]
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D -->|"NO"| WAIT["TUNGGU --- Confidence Kurang"]
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style A fill:#4a90d9,color:#fff
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style S fill:#f5a623,color:#fff
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style Q fill:#7b68ee,color:#fff
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style E fill:#27ae60,color:#fff
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style G fill:#2ecc71,color:#fff
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style M fill:#f39c12,color:#fff
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style P fill:#e67e22,color:#fff
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style AV fill:#e74c3c,color:#fff
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style ENTRY fill:#27ae60,color:#fff
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style WAIT fill:#e67e22,color:#fff
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style SKIP fill:#e74c3c,color:#fff
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```
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---
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## Prinsip Dasar
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```
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Market BAGUS (trending, session bagus) → Threshold RENDAH (60%) → Lebih banyak trade
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Market BIASA (normal) → Threshold SEDANG (70%) → Trade normal
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Market JELEK (choppy, low liquidity) → Threshold TINGGI (80%) → Sangat selektif
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Market BERBAHAYA (crisis, weekend) → Threshold MAXIMUM (85%) → Hindari trading
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Market BAGUS (trending, session bagus) --> Threshold RENDAH (60%) --> Lebih banyak trade
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Market BIASA (normal) --> Threshold SEDANG (70%) --> Trade normal
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Market JELEK (choppy, low liquidity) --> Threshold TINGGI (80%) --> Sangat selektif
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Market BERBAHAYA (crisis, weekend) --> Threshold MAXIMUM (85%) --> Hindari trading
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```
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---
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@@ -41,50 +93,50 @@ DynamicConfidenceManager(
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Score dimulai dari **50** (tengah), lalu disesuaikan oleh 6 faktor:
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### Faktor 1: Session (±20 poin)
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### Faktor 1: *Session* (+/- 20 poin)
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| Session | Poin | Alasan |
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| *Session* | Poin | Alasan |
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|---------|------|--------|
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| London-NY Overlap / Golden | **+20** | Likuiditas tertinggi, spread rendah |
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| London | **+15** | Volume tinggi |
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| New York | **+10** | Volume tinggi |
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| Asia/Tokyo | **+0** | Volatilitas rendah |
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| Asia/Tokyo | **+0** | *Volatility* rendah |
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| Market Closed/Weekend | **-30** | Tidak ada likuiditas |
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| Lainnya | **+5** | Default |
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### Faktor 2: Regime (±15 poin)
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### Faktor 2: *Regime* (+/- 15 poin)
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| Regime | Poin | Alasan |
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| *Regime* | Poin | Alasan |
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|--------|------|--------|
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| Medium Volatility | **+15** | Kondisi ideal untuk trading |
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| Low Volatility | **+5** | Hati-hati ranging |
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| High Volatility | **-5** | Perlu lot kecil |
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| Medium *Volatility* | **+15** | Kondisi ideal untuk trading |
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| Low *Volatility* | **+5** | Hati-hati *ranging* |
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| High *Volatility* | **-5** | Perlu lot kecil |
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| Crisis | **-25** | Hindari trading |
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### Faktor 3: Volatility (±10 poin)
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### Faktor 3: *Volatility* (+/- 10 poin)
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| Volatility | Poin | Alasan |
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| *Volatility* | Poin | Alasan |
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|-----------|------|--------|
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| Medium | **+10** | Pergerakan cukup, bisa diprediksi |
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| Low | **+0** | Pergerakan terlalu kecil |
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| High | **-5** | Sulit diprediksi |
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| Extreme | **-10** | Sangat berbahaya |
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### Faktor 4: Trend Clarity (±10 poin)
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### Faktor 4: Trend Clarity (+/- 10 poin)
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| Trend | Poin | Alasan |
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|-------|------|--------|
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| Uptrend / Downtrend | **+10** | Arah jelas, sinyal lebih akurat |
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| Neutral / Ranging | **-5** | Sinyal sering whipsaw |
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| Uptrend / Downtrend (*trending*) | **+10** | Arah jelas, sinyal lebih akurat |
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| Neutral / *Ranging* | **-5** | Sinyal sering whipsaw |
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### Faktor 5: SMC Confluence (±10 poin)
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### Faktor 5: SMC *Confluence* (+/- 10 poin)
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| Kondisi | Poin | Alasan |
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|---------|------|--------|
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| Ada sinyal SMC (OB/FVG/BOS) | **+10** | Konfirmasi tambahan |
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| Tidak ada sinyal | **+0** | Tanpa konfirmasi |
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### Faktor 6: ML Alignment (±5 poin)
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### Faktor 6: ML Alignment (+/- 5 poin)
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| ML Confidence | Poin | Alasan |
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|--------------|------|--------|
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@@ -94,9 +146,9 @@ Score dimulai dari **50** (tengah), lalu disesuaikan oleh 6 faktor:
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---
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## Pemetaan Score ke Quality
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## Pemetaan Score ke *Market Quality*
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Score dihitung (0–100), lalu dipetakan ke **5 level kualitas**:
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Score dihitung (0--100), lalu dipetakan ke **5 level kualitas**:
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```
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Score: 0 10 20 30 35 50 65 80 100
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@@ -106,7 +158,7 @@ Score: 0 10 20 30 35 50 65 80 100
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| thresh: 85% |80% | 70% |65% | 60%
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```
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| Score | Quality | Threshold | Aksi |
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| Score | Quality | *Threshold* | Aksi |
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|-------|---------|-----------|------|
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| **80+** | EXCELLENT | 60% | Trade dengan percaya diri |
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| **65-79** | GOOD | 65% | Trade normal |
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```
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Base score: 50
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[+20] Session: London-NY Overlap → 70
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[+15] Regime: Medium Volatility → 85
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[+10] Volatility: Medium → 95
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[+10] Trend: UPTREND → 105 → cap 100
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[+10] SMC: Ada FVG + BOS → 100
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[+5] ML: 72% confidence → 100
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[+20] Session: London-NY Overlap --> 70
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[+15] Regime: Medium Volatility --> 85
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[+10] Volatility: Medium --> 95
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[+10] Trend: UPTREND --> 105 --> cap 100
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[+10] SMC: Ada FVG + BOS --> 100
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[+5] ML: 72% confidence --> 100
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Score: 100 → EXCELLENT → Threshold: 60%
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Score: 100 --> EXCELLENT --> Threshold: 60%
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```
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**Artinya:** ML cukup confidence 60% saja untuk entry. Lebih banyak trade opportunity.
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### Contoh 2: Kondisi Jelek (Score: 40)
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### Contoh 2: Kondisi Jelek (Score: 50)
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```
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Base score: 50
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[+0] Session: Asia → 50
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[+5] Regime: Low Volatility → 55
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[+0] Volatility: Low → 55
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[-5] Trend: RANGING → 50
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[+0] SMC: Tidak ada signal → 50
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[+0] ML: 58% confidence → 50
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[+0] Session: Asia --> 50
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[+5] Regime: Low Volatility --> 55
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[+0] Volatility: Low --> 55
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[-5] Trend: RANGING --> 50
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[+0] SMC: Tidak ada signal --> 50
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[+0] ML: 58% confidence --> 50
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Score: 50 → MODERATE → Threshold: 70%
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Score: 50 --> MODERATE --> Threshold: 70%
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```
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**Artinya:** ML harus confidence 70% untuk entry. Lebih selektif.
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### Contoh 3: Kondisi Berbahaya (Score: 15)
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### Contoh 3: Kondisi Berbahaya (Score: 0)
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```
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Base score: 50
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[-30] Session: Weekend → 20
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[-25] Regime: Crisis → -5 → cap 0
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[-10] Volatility: Extreme → 0
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[-5] Trend: Ranging → 0
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[+0] SMC: Tidak ada → 0
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[+0] ML: 55% → 0
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[-30] Session: Weekend --> 20
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[-25] Regime: Crisis --> -5 --> cap 0
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[-10] Volatility: Extreme --> 0
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[-5] Trend: Ranging --> 0
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[+0] SMC: Tidak ada --> 0
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[+0] ML: 55% --> 0
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Score: 0 → AVOID → Threshold: 85% (praktis tidak trade)
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Score: 0 --> AVOID --> Threshold: 85% (praktis tidak trade)
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```
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---
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@@ -172,7 +224,7 @@ Score: 0 → AVOID → Threshold: 85% (praktis tidak trade)
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## Integrasi di Entry Flow
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```python
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# main_live.py — Step 6 dari 11 filter entry
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# main_live.py --- Step 6 dari 11 filter entry
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# 1. Analisis kondisi market
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market_analysis = dynamic_confidence.analyze_market(
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@@ -187,7 +239,7 @@ market_analysis = dynamic_confidence.analyze_market(
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# 2. Cek quality
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if market_analysis.quality == MarketQuality.AVOID:
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return # SKIP — market tidak layak
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return # SKIP --- market tidak layak
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# 3. Cek apakah ML confidence memenuhi threshold dinamis
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can_entry, reason = dynamic_confidence.get_entry_decision(
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@@ -204,7 +256,7 @@ can_entry, reason = dynamic_confidence.get_entry_decision(
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## Integrasi di Backtest
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```python
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# backtest_live_sync.py — identik dengan live
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# backtest_live_sync.py --- identik dengan live
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market_analysis = self.dynamic_confidence.analyze_market(
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session=session_name,
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@@ -229,9 +281,9 @@ def get_entry_decision(ml_confidence, analysis) -> (bool, str):
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"""
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Keputusan final entry berdasarkan analisis.
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1. Quality == AVOID? → False (jangan trade)
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2. ML confidence >= threshold? → True (entry OK)
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3. ML confidence < threshold? → False (tunggu)
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1. Quality == AVOID? --> False (jangan trade)
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2. ML confidence >= threshold? --> True (entry OK)
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3. ML confidence < threshold? --> False (tunggu)
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"""
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# Contoh output:
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@@ -247,18 +299,18 @@ def get_entry_decision(ml_confidence, analysis) -> (bool, str):
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```python
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def get_threshold_summary(analysis) -> str:
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"""
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Output: "Market: EXCELLENT (score=95) → Threshold: 60%"
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Output: "Market: EXCELLENT (score=95) --> Threshold: 60%"
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"""
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```
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Contoh log di main_live.py:
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```
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[14:30] Market: EXCELLENT (score=95) → Threshold: 60%
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[14:30] Market: EXCELLENT (score=95) --> Threshold: 60%
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[14:35] Entry OK: ML 68% >= threshold 60% (score=95)
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[15:00] Market: MODERATE (score=55) → Threshold: 70%
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[15:00] Market: MODERATE (score=55) --> Threshold: 70%
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[15:05] Wait: ML 62% < threshold 70% (need +8%)
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[04:00] Market: AVOID (score=15) → Threshold: 85%
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[04:00] Market: AVOID (score=15) --> Threshold: 85%
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```
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---
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@@ -270,26 +322,26 @@ Kondisi Market Saat Ini
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v
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6 Faktor Dianalisis:
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├── Session ±20 poin
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├── Regime ±15 poin
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├── Volatility ±10 poin
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├── Trend ±10 poin
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├── SMC ±10 poin
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└── ML ±5 poin
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+-- Session +/- 20 poin
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+-- Regime +/- 15 poin
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+-- Volatility +/- 10 poin
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+-- Trend +/- 10 poin
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+-- SMC +/- 10 poin
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+-- ML +/- 5 poin
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v
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Score (0-100)
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v
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Quality Level:
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├── EXCELLENT (80+) → Threshold 60%
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├── GOOD (65-79) → Threshold 65%
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├── MODERATE (50-64)→ Threshold 70%
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├── POOR (35-49) → Threshold 80%
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└── AVOID (<35) → Threshold 85% / SKIP
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+-- EXCELLENT (80+) --> Threshold 60%
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+-- GOOD (65-79) --> Threshold 65%
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+-- MODERATE (50-64) --> Threshold 70%
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+-- POOR (35-49) --> Threshold 80%
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+-- AVOID (<35) --> Threshold 85% / SKIP
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v
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ML Confidence >= Threshold?
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├── YES → ENTRY diizinkan
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└── NO → TUNGGU
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+-- YES --> ENTRY diizinkan
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+-- NO --> TUNGGU
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```
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Reference in New Issue
Block a user