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app.py

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+import pandas as pd
+import joblib
+import gradio as gr
+from datetime import datetime
+
+# Muat model
+model = joblib.load('random_forest_model.pkl')
+
+# Fungsi untuk memprediksi prioritas tugas
+def predict_task_duration(duration, deadline):
+    start_date = datetime(2024, 10, 20)
+    deadline_days = (pd.to_datetime(deadline) - start_date).days
+    input_data = pd.DataFrame([[duration, deadline_days]], columns=['duration', 'deadline_days'])
+    
+    # Prediksi prioritas
+    priority = model.predict(input_data)
+    return f'Prioritas Tugas: {priority[0]}'
+
+# Buat antarmuka Gradio
+iface = gr.Interface(
+    fn=predict_task_duration,
+    inputs=[
+        gr.inputs.Slider(minimum=1, maximum=10, default=5, label="Durasi Tugas (dalam jam)"),
+        gr.inputs.Textbox(placeholder="Masukkan tanggal deadline (YYYY-MM-DD)", label="Tanggal Deadline")
+    ],
+    outputs="text",
+    title="Prediksi Prioritas Tugas",
+    description="Masukkan durasi dan tanggal deadline tugas untuk memprediksi prioritasnya."
+)
+
+# Jalankan antarmuka
+iface.launch()

random_forest_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2b6d7351b0044f38a7ae08c62472113aaa4bf06522eff979ab62b3dc0e13f5b5
+size 3997617