Create app.py

app.py

@@ -0,0 +1,158 @@
+import gradio as gr
+
+def credit_scoring_model(
+    name,
+    number,
+    job,
+    income,
+    employment_status,
+    credit_history,
+    gpa
+):
+    score = 0
+    reasons = []
+
+    # ----------------------------
+    # INCOME (30%)
+    # ----------------------------
+    if income >= 15000000:
+        score += 30
+        reasons.append("Penghasilan sangat baik")
+    elif income >= 8000000:
+        score += 25
+        reasons.append("Penghasilan baik")
+    elif income >= 5000000:
+        score += 20
+        reasons.append("Penghasilan cukup")
+    else:
+        score += 10
+        reasons.append("Penghasilan rendah")
+
+    # ----------------------------
+    # EMPLOYMENT STATUS (20%)
+    # ----------------------------
+    if employment_status == "Tetap":
+        score += 20
+        reasons.append("Status pekerjaan tetap")
+    elif employment_status == "Kontrak":
+        score += 12
+        reasons.append("Status pekerjaan kontrak")
+    else:
+        score += 5
+        reasons.append("Status pekerjaan tidak tetap")
+
+    # ----------------------------
+    # CREDIT HISTORY (30%)
+    # ----------------------------
+    if credit_history == "Lancar":
+        score += 30
+        reasons.append("Riwayat kredit lancar")
+    elif credit_history == "Pernah Tunggakan":
+        score += 15
+        reasons.append("Pernah mengalami tunggakan")
+    else:
+        score += 5
+        reasons.append("Riwayat kredit buruk")
+
+    # ----------------------------
+    # GPA (20%) – OPTIONAL
+    # ----------------------------
+    if gpa >= 3.75:
+        score += 20
+        reasons.append("IPK sangat baik")
+    elif gpa >= 3.25:
+        score += 15
+        reasons.append("IPK baik")
+    elif gpa >= 3.0:
+        score += 10
+        reasons.append("IPK cukup")
+    else:
+        score += 5
+        reasons.append("IPK rendah / tidak tersedia")
+
+    # ----------------------------
+    # FINAL DECISION
+    # ----------------------------
+    if score >= 80:
+        grade = "A"
+        decision = "✅ LAYAK KREDIT"
+    elif score >= 65:
+        grade = "B"
+        decision = "🟡 DIPERTIMBANGKAN"
+    elif score >= 50:
+        grade = "C"
+        decision = "🟠 RISIKO MENENGAH"
+    else:
+        grade = "D"
+        decision = "❌ TIDAK LAYAK"
+
+    return f"""
+👤 Nama              : {name}
+📞 Nomor             : {number}
+💼 Pekerjaan         : {job}
+
+📊 HASIL CREDIT SCORING MODEL (CSM)
+---------------------------------
+Skor Total           : {score} / 100
+Grade                : {grade}
+Keputusan Kredit     : {decision}
+
+🧠 Alasan Penilaian:
+- """ + "\n- ".join(reasons) + """
+
+📌 Catatan:
+Model ini bersifat rule-based & explainable,
+sesuai untuk simulasi Bank / Fintech / Audit.
+"""
+
+# ============================
+# GRADIO UI (HF READY)
+# ============================
+with gr.Blocks() as demo:
+    gr.Markdown("## 🏦 Credit Scoring Model (CSM)")
+    gr.Markdown(
+        "Simulasi penilaian kelayakan kredit berbasis **rule-based & explainable** "
+        "(cocok untuk Bank, Fintech, Audit, dan Governance)."
+    )
+
+    with gr.Row():
+        name = gr.Textbox(label="Nama Lengkap")
+        number = gr.Textbox(label="Nomor (HP / ID)")
+
+    job = gr.Textbox(label="Pekerjaan")
+    income = gr.Number(label="Penghasilan Bulanan (Rp)", value=5000000)
+
+    with gr.Row():
+        employment_status = gr.Dropdown(
+            ["Tetap", "Kontrak", "Tidak Tetap"],
+            label="Status Pekerjaan"
+        )
+        credit_history = gr.Dropdown(
+            ["Lancar", "Pernah Tunggakan", "Buruk"],
+            label="Riwayat Kredit"
+        )
+
+    gpa = gr.Slider(2.0, 4.0, step=0.01, label="IPK (Opsional)")
+
+    output = gr.Textbox(
+        label="Hasil Analisis Credit Scoring",
+        lines=18
+    )
+
+    submit = gr.Button("🔍 Hitung Skor Kredit")
+
+    submit.click(
+        credit_scoring_model,
+        inputs=[
+            name,
+            number,
+            job,
+            income,
+            employment_status,
+            credit_history,
+            gpa
+        ],
+        outputs=output
+    )
+
+demo.launch()