| | import os |
| | import pandas as pd |
| | import numpy as np |
| | import gradio as gr |
| | import plotly.graph_objects as go |
| | from google import genai |
| |
|
| | |
| | GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") |
| | client_ai = genai.Client(api_key=GOOGLE_API_KEY) if GOOGLE_API_KEY else None |
| |
|
| | |
| | custom_css = """ |
| | @import url('https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600;700;800&display=swap'); |
| | body, .gradio-container { font-family: 'Plus Jakarta Sans', sans-serif !important; background-color: #FFFFFF !important; } |
| | |
| | .nagari-header { |
| | background: linear-gradient(135deg, #05A4DE 0%, #82C3EB 100%); |
| | padding: 35px; border-radius: 15px; border-bottom: 6px solid #F7BD87; |
| | margin-bottom: 25px; text-align: center; |
| | } |
| | .nagari-header h1 { color: #FFFFFF !important; font-weight: 800 !important; margin: 0; font-size: 2.2em; text-shadow: 2px 2px 4px rgba(0,0,0,0.2); } |
| | |
| | .card-sidebar { |
| | background: #E0EDF4; border-radius: 15px; padding: 25px; |
| | border: 1.5px solid #82C3EB; box-shadow: 0 4px 12px rgba(5, 164, 222, 0.1); |
| | } |
| | .health-badge { background: white; padding: 12px; border-radius: 8px; margin-bottom: 12px; border-left: 5px solid #05A4DE; font-size: 0.95em; } |
| | |
| | .report-card { background: white; border-radius: 12px; padding: 30px; border: 1px solid #E2E8F0; line-height: 1.8; color: #1e293b; } |
| | .nbo-box { background: #fffdf0; border: 2px solid #F7BD87; padding: 20px; border-radius: 10px; margin-top: 20px; } |
| | """ |
| |
|
| | class ArchonMasterEngine: |
| | def __init__(self): |
| | self.load_data() |
| |
|
| | def load_data(self): |
| | try: |
| | self.df_txn = pd.read_csv('transactions.csv', parse_dates=['date']).sort_values('date') |
| | self.df_cust = pd.read_csv('customers.csv') |
| | self.df_bal = pd.read_csv('balances_revised.csv', parse_dates=['month']).sort_values('month') |
| | self.df_rep = pd.read_csv('repayments_revised.csv', parse_dates=['due_date']).fillna("on_time") |
| | except Exception as e: print(f"Load Error: {e}") |
| |
|
| | def analyze(self, customer_id): |
| | cid = str(customer_id).strip().upper() |
| | u_txn = self.df_txn[self.df_txn['customer_id'] == cid].copy() |
| | u_bal = self.df_bal[self.df_bal['customer_id'] == cid].sort_values('month') |
| | u_rep = self.df_rep[self.df_rep['customer_id'] == cid] |
| | u_info_df = self.df_cust[self.df_cust['customer_id'] == cid] |
| |
|
| | if u_txn.empty or u_info_df.empty: return None |
| | u_info = u_info_df.iloc[0] |
| |
|
| | |
| | essential_keywords = ['indomaret', 'alfamart', 'listrik', 'pdam', 'telkom', 'sekolah', 'rs ', 'obat', 'cicilan', 'pinjaman', 'gaji', 'asuransi', 'grocer', 'utilities'] |
| | def classify_exp(row): |
| | desc = str(row.get('raw_description', '')).lower() |
| | return 'essential' if any(k in desc for k in essential_keywords) else 'discretionary' |
| | u_txn['expense_type'] = u_txn.apply(classify_exp, axis=1) |
| |
|
| | |
| | income_txn = u_txn[u_txn['transaction_type'] == 'credit']['amount'].sum() |
| | ref_income = max(income_txn, u_info['monthly_income']) |
| | expense = u_txn[u_txn['transaction_type'] == 'debit']['amount'].sum() |
| | er = expense / ref_income if ref_income > 0 else 1.0 |
| | |
| | |
| | er_s = 1.0 if er > 0.8 else (0.5 if er > 0.5 else 0.0) |
| | bt_s = 1.0 if len(u_bal) >= 2 and u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[0]['avg_balance'] else 0.0 |
| | od_s = 1.0 if (u_bal['min_balance'] <= 0).any() else 0.0 |
| | mp_s = 1.0 if (u_rep['status'] == 'late').any() else 0.0 |
| | |
| | score = (0.3 * er_s) + (0.2 * bt_s) + (0.2 * od_s) + (0.2 * mp_s) + 0.05 |
| | risk_lv = "HIGH" if score >= 0.7 else ("MEDIUM" if score >= 0.4 else "LOW") |
| |
|
| | |
| | if risk_lv == "HIGH" or mp_s == 1: |
| | action, nbo_msg = "Program Restrukturisasi", "Kami menyarankan penyesuaian jadwal pembayaran cicilan agar kondisi keuangan Anda tetap terjaga." |
| | steps = ["Ajukan peninjauan tenor", "Konsolidasi tagihan harian", "Manfaatkan konsultasi dana."] |
| | elif er > 0.6: |
| | action, nbo_msg = "Pengaturan Limit Belanja (Spending Control)", "Kami mendeteksi pola belanja yang tinggi. Anda disarankan mengatur limit transaksi harian agar tabungan tetap aman." |
| | steps = ["Atur limit harian QRIS", "Aktifkan notifikasi saldo", "Prioritaskan kebutuhan pokok."] |
| | elif risk_lv == "LOW": |
| | action, nbo_msg = "Optimalkan Tabungan (Promote Saving)", "Kondisi keuangan Anda sangat prima. Ini waktu yang tepat untuk menumbuhkan aset Anda melalui Deposito." |
| | steps = ["Buka tabungan berjangka", "Pindahkan dana ke deposito", "Eksplorasi produk reksa dana."] |
| | else: |
| | action, nbo_msg = "Edukasi Pengelolaan Kas", "Mari perkuat daya tahan keuangan Anda dengan tips pengelolaan arus kas di aplikasi mobile kami." |
| | steps = ["Baca artikel cerdas belanja", "Gunakan fitur budgeting", "Review pengeluaran bulanan."] |
| |
|
| | return risk_lv, score, er, u_bal, u_txn, expense, ref_income, action, nbo_msg, steps, er_s, bt_s, od_s, mp_s |
| |
|
| | def build_narrative(self, risk_lv, score, er, u_bal, exp, inc, action, nbo_msg, steps, cid, u_txn): |
| | |
| | msg = f"### LAPORAN ANALISIS RESILIENSI FINANSIAL ANDA\n\n" |
| | msg += f"Halo Bapak/Ibu, sistem Archon menetapkan tingkat kesehatan finansial Anda ({cid}) pada kategori **{risk_lv}** (Skor: {score:.2f}).\n\n" |
| | |
| | msg += f"**1. Mengapa Skor Ini Muncul?**\n" |
| | msg += f"* **Efisiensi Belanja ({er:.1%})**: Anda menghabiskan Rp{exp:,.0f} dari pendapatan Rp{inc:,.0f}. " |
| | msg += "Ini menunjukkan pengeluaran yang melebihi pendapatan (defisit)." if er > 1 else "Manajemen belanja Anda terpantau cukup terkendali." |
| | |
| | if not u_bal.empty: |
| | msg += f"\n* **Analisis Saldo**: Saldo rata-rata Anda Rp{u_bal.iloc[-1]['avg_balance']:,.0f}. " |
| | msg += "Terdeteksi tren penurunan saldo, disarankan untuk mulai menabung kembali." if len(u_bal) > 1 and u_bal.iloc[-1]['avg_balance'] < u_bal.iloc[0]['avg_balance'] else "Saldo Anda tumbuh dengan stabil dan aman." |
| |
|
| | msg += f"\n\n<div class='nbo-box'>REKOMENDASI UNTUK ANDA: {action}\n\n" |
| | msg += f"**Tujuan:** {nbo_msg}\n\n" |
| | msg += f"**Langkah-Langkah Implementasi:**\n" |
| | for i, step in enumerate(steps, 1): msg += f"{i}. {step}\n" |
| | msg += f"</div>" |
| | return msg |
| |
|
| | def create_viz(self, u_bal, u_txn): |
| | |
| | u_txn['m'] = u_txn['date'].dt.to_period('M').dt.to_timestamp() |
| | cf = u_txn.groupby(['m', 'transaction_type'])['amount'].sum().unstack().fillna(0) |
| | f1 = go.Figure() |
| | f1.add_trace(go.Bar(x=cf.index, y=cf.get('credit', 0), name='Pemasukan (Inflow)', marker_color='#82C3EB')) |
| | f1.add_trace(go.Bar(x=cf.index, y=cf.get('debit', 0), name='Pengeluaran (Outflow)', marker_color='#05A4DE')) |
| | f1.update_layout(title="Arus Kas Bulanan", barmode='group', template='plotly_white') |
| |
|
| | |
| | exp_dist = u_txn[u_txn['transaction_type'] == 'debit'].groupby('expense_type')['amount'].sum().reset_index() |
| | color_map = {'essential': '#05A4DE', 'discretionary': '#F7BD87'} |
| | f2 = go.Figure(data=[go.Pie( |
| | labels=exp_dist['expense_type'], values=exp_dist['amount'], hole=.4, |
| | marker=dict(colors=[color_map.get(x, '#E0EDF4') for x in exp_dist['expense_type']]) |
| | )]) |
| | f2.update_layout(title="Komposisi Pengeluaran (Kebutuhan vs Gaya Hidup)") |
| |
|
| | |
| | f3 = go.Figure() |
| | f3.add_trace(go.Scatter(x=u_bal['month'], y=u_bal['avg_balance'], name='Saldo Rata-rata', line=dict(color='#F7BD87', width=4))) |
| | f3.update_layout(title="Tren Pertumbuhan Saldo", template='plotly_white') |
| | |
| | return f1, f2, f3 |
| |
|
| | |
| | engine = ArchonMasterEngine() |
| |
|
| | def run_app(cust_id): |
| | res = engine.analyze(cust_id) |
| | if not res: return "ID Tidak Valid", "Gunakan ID C0001 - C0120", None, None, None |
| | |
| | risk_lv, score, er, u_bal, u_txn, exp, inc, action, nbo_msg, steps, er_s, bt_s, od_s, mp_s = res |
| | report = engine.build_narrative(risk_lv, score, er, u_bal, exp, inc, action, nbo_msg, steps, cust_id, u_txn) |
| | p1, p2, p3 = engine.create_viz(u_bal, u_txn) |
| | |
| | color = "#ef4444" if risk_lv == "HIGH" else ("#f59e0b" if risk_lv == "MEDIUM" else "#10b981") |
| | sidebar = f""" |
| | <div class='card-sidebar'> |
| | <h2 style='color: #05A4DE; margin:0;'>Status Keuangan</h2> |
| | <div style='background:{color}; color:white; padding:10px 20px; border-radius:30px; font-weight:bold; display:inline-block; margin:15px 0;'>{risk_lv} RISK LEVEL</div> |
| | <div class='health-badge'><b>Skor Risiko:</b> {score:.2f} / 1.00</div> |
| | <div class='health-badge'><b>Efisiensi Belanja:</b> {er:.1%} {'⚠️' if er > 0.8 else '✔️'}</div> |
| | <div class='health-badge'><b>Kesehatan Saldo:</b> {'🔻 Menurun' if bt_s == 1 else '🔺 Stabil'}</div> |
| | </div> |
| | """ |
| | return sidebar, report, p1, p2, p3 |
| |
|
| | with gr.Blocks(css=custom_css) as demo: |
| | gr.HTML("<div class='nagari-header'><h1>ARCHON-AI</h1></div>") |
| | with gr.Row(): |
| | with gr.Column(scale=1): |
| | id_in = gr.Textbox(label="Customer ID", placeholder="C0001") |
| | btn = gr.Button("ANALYZE CUSTOMER", variant="primary") |
| | out_side = gr.HTML() |
| | with gr.Column(scale=2): |
| | with gr.Tabs(): |
| | with gr.Tab("Laporan Untuk Anda"): |
| | out_report = gr.Markdown(elem_classes="report-card") |
| | with gr.Tab("Visualisasi Keuangan"): |
| | gr.Markdown("### 1. Uang Masuk vs Uang Keluar") |
| | plot_cf = gr.Plot() |
| | gr.HTML("<div style='background:#f1f5f9; padding:15px; border-radius:8px;'><b>Interpretasi:</b> Batang muda (Inflow) idealnya lebih tinggi dari batang tua (Outflow).</div>") |
| | gr.Markdown("---") |
| | gr.Markdown("### 2. Komposisi Gaya Hidup") |
| | plot_dist = gr.Plot() |
| | gr.HTML("<div style='background:#f1f5f9; padding:15px; border-radius:8px;'><b>Warna:</b> Biru = Kebutuhan (Essential). Emas = Gaya Hidup (Discretionary).</div>") |
| | gr.Markdown("---") |
| | gr.Markdown("### 3. Tren Pertumbuhan Saldo") |
| | plot_bal = gr.Plot() |
| | gr.HTML("<div style='background:#f1f5f9; padding:15px; border-radius:8px;'><b>Interpretasi:</b> Menunjukkan daya tahan tabungan Anda terhadap krisis.</div>") |
| |
|
| | btn.click(fn=run_app, inputs=id_in, outputs=[out_side, out_report, plot_cf, plot_dist, plot_bal]) |
| |
|
| | demo.launch() |
