new file

app.py

@@ -0,0 +1,268 @@
+from flask import Flask, render_template, request, jsonify
+import pandas as pd
+import numpy as np
+import pickle
+import os
+from datetime import datetime, timedelta
+import matplotlib
+matplotlib.use('Agg')  # Use non-interactive backend
+import matplotlib.pyplot as plt
+import seaborn as sns
+import base64
+import io
+
+app = Flask(__name__)
+
+# Load model and scaler
+def load_model_and_scaler():
+    try:
+        with open('model.pkl', 'rb') as model_file:
+            model = pickle.load(model_file)
+        
+        with open('scaler.pkl', 'rb') as scaler_file:
+            scaler = pickle.load(scaler_file)
+        
+        return model, scaler
+    except FileNotFoundError:
+        return None, None
+
+def load_data():
+    """Load and preprocess the gold data"""
+    try:
+        data = pd.read_csv('gold.csv')
+        data['date'] = pd.to_datetime(data['date'], format='%d/%m/%Y').dt.strftime('%Y-%m-%d')
+        temp_df = data[['date', 'close', 'open']]
+        
+        # Preprocessing
+        df = temp_df.copy()
+        df['date'] = pd.to_datetime(df['date'], dayfirst=True, format='%Y-%m-%d').dt.date
+        df.set_index('date', inplace=True)
+        df.index = pd.to_datetime(df.index)
+        df = df.sort_index()
+        
+        return df
+    except FileNotFoundError:
+        return None
+
+def normalize_data(df, scaler):
+    """Normalize the data using the provided scaler"""
+    np_data_unscaled = np.array(df)
+    np_data_scaled = scaler.transform(np_data_unscaled)
+    normalized_df = pd.DataFrame(np_data_scaled, columns=df.columns, index=df.index)
+    return normalized_df
+
+def sliding_window(data, lag):
+    """Create sliding window features"""
+    series_close = data['close']
+    series_open = data['open']
+    result = pd.DataFrame()
+
+    # Add lag columns for 'close'
+    for l in lag:
+        result[f'close-{l}'] = series_close.shift(l)
+
+    # Add lag columns for 'open'
+    for l in lag:
+        result[f'open-{l}'] = series_open.shift(l)
+
+    # Add original 'close' and 'open' columns
+    result['close'] = series_close[max(lag):]
+    result['open'] = series_open[max(lag):]
+
+    # Remove missing values (NaN)
+    result = result.dropna()
+
+    # Set index according to lag values
+    result.index = series_close.index[max(lag):]
+
+    return result
+
+def predict_next_7_days(model, scaler, data):
+    """Predict gold prices for the next 7 days"""
+    # Normalize data
+    normalized_df = normalize_data(data, scaler)
+    
+    # Create sliding window
+    windowed_data = sliding_window(normalized_df, [1, 2, 3, 4, 5, 6, 7])
+    windowed_data = windowed_data[['close', 'close-1', 'close-2', 'close-3', 'close-4', 'close-5', 'close-6', 'close-7', 
+                                   'open', 'open-1', 'open-2', 'open-3', 'open-4', 'open-5', 'open-6', 'open-7']]
+    
+    # Initialize predictions list
+    predictions = []
+    
+    # Get last row as initial input
+    last_row = windowed_data.drop(columns=['close', 'open']).iloc[-1].values.reshape(1, -1)
+    
+    # Iterate for 7 days
+    for _ in range(7):
+        # Predict value for next day
+        predicted_value_normalized = model.predict(last_row)
+        predicted_value = scaler.inverse_transform(predicted_value_normalized.reshape(-1, 2))
+        
+        # Save prediction
+        predictions.append(predicted_value[0])
+        
+        # Update input for next iteration
+        new_row_normalized = np.hstack([last_row[0, 2:], predicted_value_normalized[0]])
+        last_row = new_row_normalized.reshape(1, -1)
+    
+    # Transform predictions to DataFrame
+    predictions_df = pd.DataFrame(
+        predictions,
+        columns=['close', 'open'],
+        index=pd.date_range(start=normalized_df.index[-1] + pd.Timedelta(days=1), periods=7)
+    )
+    
+    # Get last price
+    last_price = scaler.inverse_transform(normalized_df[['close', 'open']].iloc[-1].values.reshape(-1, 2))
+    
+    # Calculate daily percentage changes
+    predictions_df['close_change'] = predictions_df['close'].pct_change().fillna(0) * 100
+    predictions_df['open_change'] = predictions_df['open'].pct_change().fillna(0) * 100
+    
+    # Calculate total change from today to day 7
+    total_close_change = ((predictions_df['close'].iloc[-1] - last_price[0][0]) / last_price[0][0]) * 100
+    total_open_change = ((predictions_df['open'].iloc[-1] - last_price[0][1]) / last_price[0][1]) * 100
+    
+    return predictions_df, last_price[0], total_close_change, total_open_change
+
+def create_prediction_chart(data, predictions_df, last_price):
+    """Create a chart showing historical and predicted prices"""
+    plt.style.use('default')
+    fig, ax = plt.subplots(figsize=(12, 8))
+    
+    # Plot last 30 days of historical data
+    recent_data = data.tail(30)
+    ax.plot(recent_data.index, recent_data['close'], 'b-', label='Historical Close Price', linewidth=2)
+    ax.plot(recent_data.index, recent_data['open'], 'g-', label='Historical Open Price', linewidth=2)
+    
+    # Add current day point
+    ax.plot(recent_data.index[-1], last_price[0], 'ro', markersize=8, label='Current Close Price')
+    ax.plot(recent_data.index[-1], last_price[1], 'go', markersize=8, label='Current Open Price')
+    
+    # Plot predictions
+    ax.plot(predictions_df.index, predictions_df['close'], 'r--', label='Predicted Close Price', linewidth=2, marker='o')
+    ax.plot(predictions_df.index, predictions_df['open'], 'orange', linestyle='--', label='Predicted Open Price', linewidth=2, marker='s')
+    
+    ax.set_title('Gold Price Prediction - Next 7 Days', fontsize=16, fontweight='bold')
+    ax.set_xlabel('Date', fontsize=12)
+    ax.set_ylabel('Price (IDR)', fontsize=12)
+    ax.legend()
+    ax.grid(True, alpha=0.3)
+    
+    # Format y-axis to show prices in millions
+    ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'{x/1000000:.1f}M'))
+    
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    
+    # Convert plot to base64 string
+    img_buffer = io.BytesIO()
+    plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight')
+    img_buffer.seek(0)
+    img_string = base64.b64encode(img_buffer.read()).decode()
+    plt.close()
+    
+    return img_string
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    try:
+        # Load model and scaler
+        model, scaler = load_model_and_scaler()
+        if model is None or scaler is None:
+            return jsonify({'error': 'Model or scaler not found. Please train the model first.'}), 500
+        
+        # Load data
+        data = load_data()
+        if data is None:
+            return jsonify({'error': 'Data file not found.'}), 500
+        
+        # Make predictions
+        predictions_df, last_price, total_close_change, total_open_change = predict_next_7_days(model, scaler, data)
+        
+        # Create chart
+        chart_img = create_prediction_chart(data, predictions_df, last_price)
+        
+        # Prepare response data
+        predictions_list = []
+        for date, row in predictions_df.iterrows():
+            predictions_list.append({
+                'date': date.strftime('%Y-%m-%d'),
+                'close_price': round(row['close'], 2),
+                'open_price': round(row['open'], 2),
+                'close_change': round(row['close_change'], 2),
+                'open_change': round(row['open_change'], 2)
+            })
+        
+        response = {
+            'success': True,
+            'current_prices': {
+                'close': round(last_price[0], 2),
+                'open': round(last_price[1], 2)
+            },
+            'predictions': predictions_list,
+            'total_changes': {
+                'close': round(total_close_change, 2),
+                'open': round(total_open_change, 2)
+            },
+            'chart': chart_img
+        }
+        
+        return jsonify(response)
+    
+    except Exception as e:
+        return jsonify({'error': f'An error occurred: {str(e)}'}), 500
+
+@app.route('/data-analysis')
+def data_analysis():
+    """Show data analysis page"""
+    try:
+        data = load_data()
+        if data is None:
+            return render_template('error.html', error='Data file not found.')
+        
+        # Create historical price chart
+        fig, ax = plt.subplots(figsize=(12, 6))
+        ax.plot(data.index, data['close'], 'b-', label='Close Price', linewidth=1.5)
+        ax.plot(data.index, data['open'], 'g-', label='Open Price', linewidth=1.5)
+        ax.set_title('Historical Gold Prices', fontsize=16, fontweight='bold')
+        ax.set_xlabel('Date', fontsize=12)
+        ax.set_ylabel('Price (IDR)', fontsize=12)
+        ax.legend()
+        ax.grid(True, alpha=0.3)
+        ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f'{x/1000000:.1f}M'))
+        plt.xticks(rotation=45)
+        plt.tight_layout()
+        
+        img_buffer = io.BytesIO()
+        plt.savefig(img_buffer, format='png', dpi=150, bbox_inches='tight')
+        img_buffer.seek(0)
+        historical_chart = base64.b64encode(img_buffer.read()).decode()
+        plt.close()
+        
+        # Calculate statistics
+        stats = {
+            'total_records': len(data),
+            'date_range': f"{data.index.min().strftime('%Y-%m-%d')} to {data.index.max().strftime('%Y-%m-%d')}",
+            'avg_close': round(data['close'].mean(), 2),
+            'avg_open': round(data['open'].mean(), 2),
+            'min_close': round(data['close'].min(), 2),
+            'max_close': round(data['close'].max(), 2),
+            'current_close': round(data['close'].iloc[-1], 2),
+            'current_open': round(data['open'].iloc[-1], 2)
+        }
+        
+        return render_template('data_analysis.html', chart=historical_chart, stats=stats)
+    
+    except Exception as e:
+        return render_template('error.html', error=f'An error occurred: {str(e)}')
+
+if __name__ == '__main__':
+    # For Hugging Face Spaces, use port 7860
+    port = int(os.environ.get('PORT', 7860))
+    app.run(host='0.0.0.0', port=port, debug=False)

gold.csv

@@ -0,0 +1,821 @@
+date,close,open,Tertinggi,Terendah,Volume,Perubahan
+12/3/2025,2932,2922,2935,2912,"112,85K","0,39%"
+11/3/2025,2921,2893,2929,2883,"2,96K","0,74%"
+10/3/2025,2899,2920,2926,2885,"221,61K","-0,5%"
+7/3/2025,2914,2919,2939,2905,"237,58K","-0,43%"
+6/3/2025,2927,2930,2936,2898,"166,36K","0,02%"
+5/3/2025,2926,2929,2941,2903,"183,02K","0,18%"
+4/3/2025,2921,2904,2940,2893,"188,52K","0,67%"
+3/3/2025,2901,2872,2906,2866,"177,02K","1,85%"
+28/02/2025,2849,2889,2896,2844,"210,56K","-1,64%"
+27/02/2025,2896,2931,2936,2879,"207,65K","-0,75%"
+26/02/2025,2918,2916,2926,2891,"2,05K","0,41%"
+25/02/2025,2906,2956,2956,2885,"5,59K","-1,48%"
+24/02/2025,2950,2939,2960,2926,"2,00K","-0,12%"
+21/02/2025,2953,2956,2965,2930,"163,69K","-0,1%"
+20/02/2025,2956,2950,2973,2939,"172,20K","0,68%"
+19/02/2025,2936,2954,2964,2934,"159,34K","-0,44%"
+18/02/2025,2949,2895,2957,2888,"218,76K","1,67%"
+14/02/2025,2901,2957,2964,2890,"228,08K","-1,52%"
+13/02/2025,2945,2929,2959,2926,"169,50K","0,57%"
+12/2/2025,2929,2927,2937,2887,"204,63K","-0,13%"
+11/2/2025,2933,2937,2969,2907,"218,48K","-0,06%"
+10/2/2025,2934,2885,2938,2880,"167,23K","1,62%"
+7/2/2025,2888,2880,2911,2876,"192,55K","0,38%"
+6/2/2025,2877,2885,2894,2855,"167,70K","-0,56%"
+5/2/2025,2893,2874,2906,2870,"167,38K","0,6%"
+4/2/2025,2876,2850,2877,2837,"145,86K","0,65%"
+3/2/2025,2857,2847,2872,2802,"181,34K","0,78%"
+31/01/2025,2835,2852,2863,2826,"165,68K","-0,36%"
+30/01/2025,2845,2796,2853,2795,"188,34K","2,29%"
+29/01/2025,2782,2785,2790,2773,"3,98K","0,02%"
+28/01/2025,2781,2757,2787,2753,"3,42K","1,04%"
+27/01/2025,2752,2791,2791,2747,"3,94K","-1,44%"
+24/01/2025,2793,2779,2808,2779,"1,10K","0,52%"
+23/01/2025,2778,2778,2780,2755,"1,83K","-0,68%"
+22/01/2025,2797,2785,2800,2783,"39,59K","0,42%"
+21/01/2025,2786,2766,2788,2742,"56,80K","1,34%"
+17/01/2025,2749,2747,2759,2729,"156,87K","-0,08%"
+16/01/2025,2751,2722,2758,2720,"186,54K","1,22%"
+15/01/2025,2718,2693,2723,2685,"193,72K","1,32%"
+14/01/2025,2682,2682,2694,2672,"179,41K","0,14%"
+13/01/2025,2679,2717,2724,2675,"211,09K","-1,34%"
+10/1/2025,2715,2693,2735,2687,"298,41K","0,9%"
+9/1/2025,2691,2680,2697,2674,"156,65K","0,69%"
+8/1/2025,2672,2663,2687,2658,"197,37K","0,26%"
+7/1/2025,2665,2647,2679,2644,"161,62K","0,68%"
+6/1/2025,2647,2653,2664,2625,"169,92K","-0,27%"
+3/1/2025,2655,2671,2681,2650,"121,17K","-0,54%"
+2/1/2025,2669,2641,2674,2636,"144,52K","1,06%"
+31/12/2024,2641,2620,2642,2614,"86,29K","0,87%"
+30/12/2024,2618,2636,2641,2608,"110,92K","-0,01%"
+27/12/2024,2618,2640,2640,2612,"0,64K","-0,83%"
+26/12/2024,2640,2623,2642,2623,"1,40K","0,67%"
+24/12/2024,2623,2617,2623,2613,"0,42K","0,28%"
+23/12/2024,2616,2627,2633,2610,"0,56K","-0,65%"
+20/12/2024,2633,2598,2641,2596,"0,51K","1,41%"
+19/12/2024,2596,2586,2625,2586,"0,90K","-1,7%"
+18/12/2024,2641,2651,2654,2587,"0,88K","-0,33%"
+17/12/2024,2650,2657,2663,2634,"0,63K","-0,28%"
+16/12/2024,2657,2655,2670,2648,"1,41K","-0,2%"
+13/12/2024,2662,2690,2702,2651,"1,07K","-1,21%"
+12/12/2024,2695,2738,2744,2683,"1,69K","-1,69%"
+11/12/2024,2742,2709,2744,2700,"3,82K","1,33%"
+10/12/2024,2706,2670,2709,2670,"1,41K","1,21%"
+9/12/2024,2673,2655,2687,2638,"0,96K","0,99%"
+6/12/2024,2647,2642,2655,2630,"0,80K","0,42%"
+5/12/2024,2636,2662,2667,2635,"1,67K","-1,06%"
+4/12/2024,2664,2651,2670,2644,"0,85K","0,32%"
+3/12/2024,2656,2652,2665,2645,"0,61K","0,36%"
+2/12/2024,2647,2664,2664,2634,"0,97K","-0,84%"
+29/11/2024,2669,2650,2678,2632,"1,35K","0,63%"
+27/11/2024,2652,2646,2671,2641,"2,27K","1,18%"
+26/11/2024,2621,2626,2643,2605,"177,86K","0,11%"
+25/11/2024,2619,2717,2723,2617,"305,34K","-3,45%"
+22/11/2024,2712,2672,2719,2670,"220,55K","1,39%"
+21/11/2024,2675,2654,2677,2652,"186,30K","0,87%"
+20/11/2024,2652,2636,2659,2622,"182,01K","0,79%"
+19/11/2024,2631,2616,2643,2614,"202,24K","0,63%"
+18/11/2024,2615,2572,2620,2569,"195,29K","1,73%"
+15/11/2024,2570,2570,2581,2559,"179,89K","-0,11%"
+14/11/2024,2573,2578,2586,2542,"266,16K","-0,53%"
+13/11/2024,2587,2605,2625,2578,"262,75K","-0,76%"
+12/11/2024,2606,2626,2633,2596,"282,77K","-0,44%"
+11/11/2024,2618,2692,2693,2617,"281,92K","-2,86%"
+8/11/2024,2695,2714,2718,2687,"233,11K","-0,41%"
+7/11/2024,2706,2668,2718,2650,"292,92K","1,1%"
+6/11/2024,2676,2753,2759,2661,"361,31K","-2,67%"
+5/11/2024,2750,2746,2760,2733,"151,43K","0,13%"
+4/11/2024,2746,2744,2758,2739,"145,25K","-0,11%"
+1/11/2024,2749,2754,2772,2743,"180,66K",0.00%
+31/10/2024,2749,2799,2801,2742,"242,57K","-1,84%"
+30/10/2024,2801,2787,2802,2782,"191,55K","1,16%"
+29/10/2024,2769,2742,2773,2742,"0,85K","0,92%"
+28/10/2024,2744,2739,2746,2726,"0,57K","0,05%"
+25/10/2024,2742,2735,2747,2717,"0,26K","0,21%"
+24/10/2024,2737,2717,2743,2717,"0,34K","0,71%"
+23/10/2024,2717,2749,2759,2710,"0,65K","-1,1%"
+22/10/2024,2747,2723,2750,2722,"0,43K","0,76%"
+21/10/2024,2727,2724,2743,2717,"0,41K","0,32%"
+18/10/2024,2718,2696,2726,2696,"0,22K","0,83%"
+17/10/2024,2696,2677,2701,2677,"0,27K","0,6%"
+16/10/2024,2679,2667,2690,2666,"0,38K","0,46%"
+15/10/2024,2667,2655,2674,2643,"0,24K","0,5%"
+14/10/2024,2654,2660,2671,2648,"0,39K","-0,4%"
+11/10/2024,2664,2634,2667,2634,"0,31K","1,41%"
+10/10/2024,2627,2615,2637,2609,"0,88K","0,51%"
+9/10/2024,2614,2629,2631,2612,"0,77K","-0,36%"
+8/10/2024,2624,2650,2660,2613,"1,05K","-1,15%"
+7/10/2024,2654,2659,2667,2646,"0,39K","-0,08%"
+4/10/2024,2656,2663,2678,2642,"0,85K","-0,43%"
+3/10/2024,2667,2668,2671,2647,"0,65K","0,35%"
+2/10/2024,2658,2671,2672,2653,"0,34K","-0,76%"
+1/10/2024,2679,2644,2682,2644,"0,46K","1,16%"
+30/09/2024,2648,2668,2675,2637,"0,55K","-0,32%"
+27/09/2024,2657,2682,2684,2655,"0,64K","-0,52%"
+26/09/2024,2670,2657,2684,2653,"17,22K","0,36%"
+25/09/2024,2661,2659,2671,2650,"21,76K","0,29%"
+24/09/2024,2653,2629,2665,2624,"13,09K","0,93%"
+23/09/2024,2629,2623,2636,2615,"8,70K","0,24%"
+20/09/2024,2622,2588,2627,2585,"9,30K","1,22%"
+19/09/2024,2591,2562,2597,2552,"8,60K","0,62%"
+18/09/2024,2575,2573,2604,2549,"10,66K","0,23%"
+17/09/2024,2569,2586,2590,2564,"6,95K","-0,63%"
+16/09/2024,2585,2585,2593,2579,"4,57K","-0,06%"
+13/09/2024,2587,2565,2591,2562,"10,05K","1,16%"
+12/9/2024,2557,2518,2565,2516,"9,29K","1,51%"
+11/9/2024,2519,2522,2534,2506,"4,91K","-0,02%"
+10/9/2024,2520,2512,2524,2506,"5,90K","0,41%"
+9/9/2024,2509,2503,2513,2491,"4,64K","0,31%"
+6/9/2024,2502,2524,2536,2491,"6,27K","-0,72%"
+5/9/2024,2520,2502,2531,2501,"6,72K","0,68%"
+4/9/2024,2503,2500,2508,2480,"5,94K","0,12%"
+3/9/2024,2500,2509,2516,2482,"10,28K","-0,19%"
+30/08/2024,2505,2531,2536,2504,"6,48K","-1,27%"
+29/08/2024,2537,2517,2539,2514,"10,79K","1,36%"
+28/08/2024,2503,2525,2526,2493,"2,35K","-0,6%"
+27/08/2024,2518,2518,2525,2504,"0,65K","-0,1%"
+26/08/2024,2520,2513,2528,2509,"0,66K","0,36%"
+23/08/2024,2511,2486,2519,2486,"0,75K","1,17%"
+22/08/2024,2482,2516,2516,2473,"0,74K","-1,22%"
+21/08/2024,2513,2517,2522,2495,"0,60K","-0,13%"
+20/08/2024,2516,2508,2535,2502,"0,66K","0,37%"
+19/08/2024,2507,2513,2514,2489,"0,78K","0,13%"
+16/08/2024,2504,2460,2514,2455,"0,59K","1,83%"
+15/08/2024,2459,2452,2472,2437,"0,53K","0,51%"
+14/08/2024,2446,2471,2485,2443,"0,56K","-1,12%"
+13/08/2024,2474,2477,2483,2464,"0,37K","0,16%"
+12/8/2024,2470,2436,2478,2430,"0,73K","1,23%"
+9/8/2024,2440,2432,2442,2424,"0,70K","0,39%"
+8/8/2024,2430,2390,2434,2388,"0,58K","1,26%"
+7/8/2024,2400,2399,2414,2387,"0,46K","0,05%"
+6/8/2024,2399,2421,2431,2390,"0,50K","-0,53%"
+5/8/2024,2412,2459,2466,2374,"1,13K",-1.00%
+2/8/2024,2436,2456,2488,2421,"2,46K","-0,4%"
+1/8/2024,2446,2459,2471,2439,"1,15K","0,3%"
+31/07/2024,2439,2421,2461,2415,"1,32K","0,86%"
+30/07/2024,2418,2393,2422,2389,"3,57K","1,67%"
+29/07/2024,2378,2387,2402,2367,"126,41K","-0,13%"
+26/07/2024,2381,2364,2390,2355,"154,52K","1,17%"
+25/07/2024,2354,2398,2401,2352,"294,90K","-2,57%"
+24/07/2024,2416,2411,2433,2397,"245,88K","0,35%"
+23/07/2024,2407,2398,2414,2389,"171,19K","0,53%"
+22/07/2024,2395,2404,2414,2385,"197,56K","-0,18%"
+19/07/2024,2399,2448,2448,2396,"254,41K","-2,33%"
+18/07/2024,2456,2463,2479,2443,"192,77K","-0,14%"
+17/07/2024,2460,2473,2488,2456,"259,54K","-0,32%"
+16/07/2024,2468,2427,2475,2425,"246,09K","1,6%"
+15/07/2024,2429,2419,2445,2406,"193,54K","0,34%"
+12/7/2024,2421,2421,2423,2396,"220,93K","-0,05%"
+11/7/2024,2422,2377,2430,2377,"303,52K","1,77%"
+10/7/2024,2380,2371,2393,2370,"163,90K","0,5%"
+9/7/2024,2368,2367,2378,2356,"252,49K","0,19%"
+8/7/2024,2364,2396,2399,2358,"240,78K","-1,43%"
+5/7/2024,2398,2366,2402,2356,"293,25K","1,4%"
+4/7/2024,2365,2367,2371,2359,,"-0,2%"
+3/7/2024,2369,2339,2375,2336,"193,64K","1,54%"
+2/7/2024,2333,2342,2346,2327,"153,71K","-0,24%"
+1/7/2024,2339,2336,2349,2328,"142,60K","-0,03%"
+28/06/2024,2340,2339,2351,2330,"135,38K","0,13%"
+27/06/2024,2337,2309,2342,2307,"140,23K","1,55%"
+26/06/2024,2301,2319,2321,2293,"0,99K","-0,75%"
+25/06/2024,2318,2334,2336,2315,"1,26K","-0,6%"
+24/06/2024,2332,2322,2335,2318,"0,60K","0,57%"
+21/06/2024,2319,2362,2370,2318,"0,60K","-1,61%"
+20/06/2024,2357,2331,2367,2327,"0,83K","0,6%"
+19/06/2024,2343,2343,2350,2339,,"0,35%"
+18/06/2024,2335,2323,2335,2309,"0,39K","0,77%"
+17/06/2024,2317,2336,2336,2312,"0,45K","-0,86%"
+14/06/2024,2337,2306,2339,2306,"0,42K","1,35%"
+13/06/2024,2306,2328,2330,2299,"0,65K","-1,57%"
+12/6/2024,2343,2322,2345,2316,"0,60K","1,21%"
+11/6/2024,2315,2316,2325,2303,"0,79K","-0,02%"
+10/6/2024,2315,2300,2319,2293,"0,75K","0,08%"
+7/6/2024,2313,2384,2394,2293,"1,30K","-2,76%"
+6/6/2024,2379,2364,2385,2361,"0,88K","0,65%"
+5/6/2024,2364,2336,2365,2335,"0,59K","1,19%"
+4/6/2024,2336,2360,2361,2325,"1,40K","-0,92%"
+3/6/2024,2358,2335,2364,2324,"0,77K","1,01%"
+31/05/2024,2334,2352,2369,2330,"1,21K","-0,88%"
+30/05/2024,2355,2358,2361,2332,"2,72K","0,58%"
+29/05/2024,2341,2363,2364,2334,"119,32K","-0,65%"
+28/05/2024,2357,2338,2366,2334,"316,22K",0.00%
+27/05/2024,2357,2338,2366,2334,"105,47K","0,94%"
+24/05/2024,2335,2330,2349,2326,"178,34K","-0,12%"
+23/05/2024,2337,2383,2386,2328,"273,66K","-2,33%"
+22/05/2024,2393,2425,2431,2378,"253,85K","-1,36%"
+21/05/2024,2426,2432,2438,2409,"229,42K","-0,52%"
+20/05/2024,2439,2422,2454,2411,"281,43K","0,87%"
+17/05/2024,2417,2381,2427,2378,"218,55K","1,34%"
+16/05/2024,2386,2392,2403,2375,"191,03K","-0,39%"
+15/05/2024,2395,2363,2396,2357,"249,84K","1,48%"
+14/05/2024,2360,2342,2365,2341,"192,08K","0,72%"
+13/05/2024,2343,2369,2371,2338,"243,08K","-1,35%"
+10/5/2024,2375,2354,2385,2352,"275,24K","1,48%"
+9/5/2024,2340,2317,2354,2313,"249,09K","0,78%"
+8/5/2024,2322,2322,2330,2311,"214,69K","-0,08%"
+7/5/2024,2324,2335,2339,2318,"204,62K","-0,3%"
+6/5/2024,2331,2313,2342,2301,"191,90K","0,98%"
+3/5/2024,2309,2314,2331,2285,"231,40K","-0,04%"
+2/5/2024,2310,2330,2336,2294,"193,66K","-0,06%"
+1/5/2024,2311,2298,2340,2292,"227,38K","0,35%"
+30/04/2024,2303,2347,2348,2296,"229,06K","-2,32%"
+29/04/2024,2358,2348,2359,2331,"187,31K","0,97%"
+26/04/2024,2335,2333,2351,2327,"0,72K","0,2%"
+25/04/2024,2330,2318,2345,2306,"0,99K","0,18%"
+24/04/2024,2326,2324,2338,2314,"0,78K","-0,17%"
+23/04/2024,2330,2332,2336,2294,"0,79K","-0,2%"
+22/04/2024,2335,2392,2392,2327,"1,03K","-2,78%"
+19/04/2024,2401,2381,2418,2375,"1,61K","0,65%"
+18/04/2024,2386,2366,2396,2366,"2,55K","0,4%"
+17/04/2024,2376,2388,2400,2360,"0,58K","-0,81%"
+16/04/2024,2396,2387,2402,2367,"1,27K","1,04%"
+15/04/2024,2371,2357,2392,2330,"1,67K","0,38%"
+12/4/2024,2362,2378,2437,2338,"2,20K","0,05%"
+11/4/2024,2361,2341,2383,2332,"0,98K","1,04%"
+10/4/2024,2337,2359,2366,2326,"1,62K","-0,6%"
+9/4/2024,2351,2344,2373,2344,"1,56K","0,5%"
+8/4/2024,2339,2332,2357,2311,"1,31K","0,23%"
+5/4/2024,2334,2299,2338,2277,"0,91K","1,6%"
+4/4/2024,2297,2309,2312,2288,"0,99K","-0,28%"
+3/4/2024,2303,2290,2310,2275,"1,23K","1,45%"
+2/4/2024,2270,2260,2290,2256,"1,70K","1,09%"
+1/4/2024,2246,2244,2275,2239,"1,10K","0,84%"
+28/03/2024,2227,2204,2244,2196,"1,62K","1,17%"
+27/03/2024,2201,2189,2207,2183,"1,21K","1,11%"
+26/03/2024,2177,2173,2201,2168,"202,37K","0,04%"
+25/03/2024,2176,2167,2183,2164,"211,61K","0,76%"
+22/03/2024,2160,2183,2188,2158,"205,81K","-1,13%"
+21/03/2024,2185,2190,2225,2168,"391,75K","1,1%"
+20/03/2024,2161,2161,2192,2152,"233,57K","0,06%"
+19/03/2024,2160,2164,2166,2150,"178,16K","-0,21%"
+18/03/2024,2164,2160,2167,2149,"211,86K","0,13%"
+15/03/2024,2162,2166,2177,2159,"187,85K","-0,28%"
+14/03/2024,2168,2180,2181,2157,"207,23K","-0,61%"
+13/03/2024,2181,2164,2186,2161,"232,27K","0,68%"
+12/3/2024,2166,2189,2191,2156,"316,25K","-1,03%"
+11/3/2024,2189,2188,2196,2181,"242,42K","0,14%"
+8/3/2024,2186,2167,2203,2161,"389,68K","0,94%"
+7/3/2024,2165,2157,2172,2152,"267,80K","0,32%"
+6/3/2024,2158,2136,2161,2132,"319,76K","0,76%"
+5/3/2024,2142,2123,2151,2119,"283,15K","0,73%"
+4/3/2024,2126,2092,2128,2088,"328,25K","1,46%"
+1/3/2024,2096,2053,2097,2047,"330,59K",2.00%
+29/02/2024,2055,2044,2059,2036,"227,07K","0,59%"
+28/02/2024,2043,2040,2047,2033,"137,08K","0,41%"
+27/02/2024,2034,2031,2038,2029,"0,96K","0,26%"
+26/02/2024,2029,2034,2036,2025,"1,14K","-0,51%"
+23/02/2024,2039,2024,2042,2016,"0,71K","0,92%"
+22/02/2024,2021,2027,2035,2020,"1,66K","-0,18%"
+21/02/2024,2025,2025,2033,2022,"1,09K","-0,27%"
+20/02/2024,2030,2018,2032,2016,"1,11K","-0,48%"
+19/02/2024,2040,2028,2043,2024,"202,43K","1,26%"
+16/02/2024,2014,2007,2017,1997,"0,80K","0,45%"
+15/02/2024,2005,1995,2010,1993,"1,07K","0,53%"
+14/02/2024,1995,1995,1999,1987,"1,63K","-0,15%"
+13/02/2024,1998,2024,2036,1993,"1,47K","-1,27%"
+12/2/2024,2023,2031,2031,2016,"1,22K","-0,27%"
+9/2/2024,2029,2039,2042,2025,"0,53K","-0,46%"
+8/2/2024,2038,2041,2044,2025,"0,67K","-0,18%"
+7/2/2024,2042,2042,2051,2037,"0,51K","0,01%"
+6/2/2024,2042,2032,2045,2029,"0,63K","0,42%"
+5/2/2024,2033,2048,2048,2021,"1,00K","-0,54%"
+2/2/2024,2044,2062,2065,2035,"3,02K","-0,84%"
+1/2/2024,2061,2048,2073,2037,"1,35K","0,18%"
+31/01/2024,2057,2045,2064,2039,"1,43K","0,8%"
+30/01/2024,2041,2042,2057,2038,"1,12K","0,78%"
+29/01/2024,2025,2024,2037,2019,"150,71K","0,4%"
+26/01/2024,2017,2021,2028,2016,"119,59K","-0,02%"
+25/01/2024,2018,2015,2026,2004,"196,67K","0,09%"
+24/01/2024,2016,2031,2038,2012,"234,46K","-0,48%"
+23/01/2024,2026,2023,2039,2021,"156,70K","0,18%"
+22/01/2024,2022,2032,2034,2017,"152,76K","-0,35%"
+19/01/2024,2029,2027,2042,2022,"172,81K","0,38%"
+18/01/2024,2022,2009,2026,2008,"171,93K","0,75%"
+17/01/2024,2007,2032,2036,2005,"254,29K","-1,17%"
+16/01/2024,2030,2053,2063,2028,"285,25K",0.00%
+15/01/2024,2030,2053,2063,2028,"285,25K","-1,04%"
+12/1/2024,2052,2033,2067,2033,"272,35K","1,6%"
+11/1/2024,2019,2029,2056,2017,"301,34K","-0,42%"
+10/1/2024,2028,2036,2046,2026,"205,01K","-0,26%"
+9/1/2024,2033,2035,2049,2032,"218,75K","-0,02%"
+8/1/2024,2034,2053,2053,2023,"220,99K","-0,8%"
+5/1/2024,2050,2051,2071,2031,"214,68K","-0,01%"
+4/1/2024,2050,2049,2058,2043,"130,26K","0,35%"
+3/1/2024,2043,2068,2074,2038,"221,68K","-1,48%"
+2/1/2024,2073,2073,2088,2064,"157,56K","0,08%"
+29/12/2023,2072,2076,2084,2068,"105,72K","-0,56%"
+28/12/2023,2084,2090,2098,2075,"129,54K",0.00%
+27/12/2023,2083,2068,2085,2063,"0,59K","1,12%"
+26/12/2023,2060,2056,2070,2056,"0,29K","0,04%"
+22/12/2023,2060,2052,2072,2049,"0,44K","0,87%"
+21/12/2023,2042,2035,2048,2034,"0,54K","0,18%"
+20/12/2023,2038,2044,2046,2032,"0,26K","-0,22%"
+19/12/2023,2043,2031,2050,2025,"0,47K","0,58%"
+18/12/2023,2031,2024,2036,2021,"0,25K","0,24%"
+15/12/2023,2026,2038,2050,2020,"0,63K","-0,45%"
+14/12/2023,2035,2032,2053,2031,"0,56K","2,37%"
+13/12/2023,1988,1986,2033,1979,"2,22K","0,21%"
+12/12/2023,1984,1989,2003,1984,"0,57K","-0,02%"
+11/12/2023,1984,2011,2013,1982,"0,55K","-1,03%"
+8/12/2023,2005,2035,2040,2001,"1,37K","-1,57%"
+7/12/2023,2037,2035,2047,2027,"0,53K","-0,07%"
+6/12/2023,2038,2028,2043,2027,"0,68K","0,57%"
+5/12/2023,2027,2039,2050,2020,"1,42K","-0,3%"
+4/12/2023,2033,2083,2141,2030,"2,70K","-2,28%"
+1/12/2023,2080,2049,2086,2043,"2,01K","1,6%"
+30/11/2023,2048,2056,2058,2043,"1,15K","-0,48%"
+29/11/2023,2058,2053,2062,2048,"1,91K","0,86%"
+28/11/2023,2040,2014,2044,2012,"174,67K","1,37%"
+27/11/2023,2012,2003,2019,2001,"251,25K","0,47%"
+24/11/2023,2003,1991,2005,1991,"214,88K",0.00%
+23/11/2023,2003,1991,2005,1991,"214,88K","0,51%"
+22/11/2023,1993,2000,2008,1989,"199,37K","-0,44%"
+21/11/2023,2002,1980,2010,1980,"230,02K","1,08%"
+20/11/2023,1980,1981,1988,1967,"177,89K","-0,22%"
+17/11/2023,1985,1984,1996,1981,"133,12K","-0,13%"
+16/11/2023,1987,1963,1991,1959,"186,81K","1,17%"
+15/11/2023,1964,1967,1979,1959,"142,92K","-0,11%"
+14/11/2023,1967,1950,1975,1939,"180,74K","0,84%"
+13/11/2023,1950,1943,1954,1936,"183,70K","0,65%"
+10/11/2023,1938,1964,1966,1937,"229,64K","-1,63%"
+9/11/2023,1970,1956,1972,1948,"214,08K","0,61%"
+8/11/2023,1958,1975,1978,1953,"189,36K","-0,8%"
+7/11/2023,1974,1985,1985,1963,"218,95K","-0,76%"
+6/11/2023,1989,1999,2000,1984,"146,28K","-0,53%"
+3/11/2023,1999,1994,2012,1989,"222,19K","0,29%"
+2/11/2023,1994,1992,1999,1986,"158,65K","0,3%"
+1/11/2023,1988,1993,2006,1978,"197,63K","-0,34%"
+31/10/2023,1994,2006,2018,1987,"214,78K","-0,56%"
+30/10/2023,2006,2014,2017,2000,"181,34K","0,83%"
+27/10/2023,1989,1988,2010,1979,"0,37K","0,06%"
+26/10/2023,1988,1982,1993,1974,"0,20K","0,12%"
+25/10/2023,1986,1972,1989,1971,"0,16K","0,44%"
+24/10/2023,1977,1975,1980,1958,"1,23K","-0,07%"
+23/10/2023,1978,1978,1983,1964,"0,45K","-0,34%"
+20/10/2023,1985,1977,1999,1976,"1,03K","0,7%"
+19/10/2023,1971,1950,1981,1948,"1,37K","0,63%"
+18/10/2023,1959,1927,1966,1927,"0,33K","1,68%"
+17/10/2023,1926,1923,1934,1918,"0,28K","0,07%"
+16/10/2023,1925,1932,1932,1912,"0,47K","-0,36%"
+13/10/2023,1932,1875,1935,1875,"0,89K","3,09%"
+12/10/2023,1874,1880,1889,1872,"0,40K","-0,22%"
+11/10/2023,1878,1865,1882,1864,"0,48K","0,63%"
+10/10/2023,1867,1866,1870,1858,"0,36K","0,59%"
+9/10/2023,1856,1851,1868,1849,"0,82K","1,03%"
+6/10/2023,1837,1826,1840,1815,"0,65K","0,74%"
+5/10/2023,1823,1828,1834,1818,"0,43K","-0,16%"
+4/10/2023,1826,1829,1836,1823,"0,51K","-0,35%"
+3/10/2023,1833,1836,1840,1823,"0,43K","-0,3%"
+2/10/2023,1838,1854,1855,1834,"0,82K","-1,01%"
+29/09/2023,1857,1873,1887,1853,"0,92K","-0,67%"
+28/09/2023,1870,1885,1887,1866,"0,90K","-0,15%"
+27/09/2023,1872,1900,1903,1872,"12,25K","-1,54%"
+26/09/2023,1902,1917,1917,1899,"12,74K","-0,87%"
+25/09/2023,1918,1926,1928,1916,"7,99K","-0,47%"
+22/09/2023,1927,1922,1931,1922,"3,30K","0,31%"
+21/09/2023,1921,1933,1934,1915,"5,62K","-1,41%"
+20/09/2023,1949,1935,1950,1930,"6,22K","0,69%"
+19/09/2023,1935,1937,1940,1933,"2,81K","0,01%"
+18/09/2023,1935,1928,1937,1926,"3,19K","0,38%"
+15/09/2023,1928,1914,1934,1913,"4,75K","0,71%"
+14/09/2023,1914,1913,1916,1904,"5,99K",0.00%
+13/09/2023,1914,1918,1920,1910,"4,87K","-0,15%"
+12/9/2023,1917,1927,1929,1912,"4,77K","-0,62%"
+11/9/2023,1929,1926,1937,1922,"3,09K","0,24%"
+8/9/2023,1925,1926,1936,1923,"6,62K","0,03%"
+7/9/2023,1924,1923,1929,1922,"4,06K","-0,09%"
+6/9/2023,1926,1933,1936,1922,"5,41K","-0,44%"
+5/9/2023,1934,1948,1954,1932,"7,21K","-0,94%"
+4/9/2023,1953,1967,1973,1951,"192,79K","0,22%"
+1/9/2023,1948,1948,1961,1942,"6,26K","0,07%"
+31/08/2023,1947,1952,1956,1947,"4,06K","-0,36%"
+30/08/2023,1954,1948,1958,1944,"6,33K","0,91%"
+29/08/2023,1936,1920,1937,1914,"1,67K","0,93%"
+28/08/2023,1919,1915,1926,1912,"0,39K","0,35%"
+25/08/2023,1912,1916,1921,1903,"0,79K","-0,38%"
+24/08/2023,1919,1919,1923,1912,"1,29K","-0,07%"
+23/08/2023,1921,1899,1922,1899,"0,92K","1,15%"
+22/08/2023,1899,1896,1906,1891,"1,02K","0,15%"
+21/08/2023,1896,1891,1900,1886,"1,27K","0,37%"
+18/08/2023,1889,1891,1898,1888,"0,61K","0,08%"
+17/08/2023,1887,1895,1905,1887,"0,71K","-0,68%"
+16/08/2023,1900,1905,1910,1894,"0,39K","-0,35%"
+15/08/2023,1907,1911,1915,1900,"0,37K","-0,45%"
+14/08/2023,1916,1915,1919,1906,"0,61K","-0,13%"
+11/8/2023,1918,1916,1925,1914,"0,46K","-0,11%"
+10/8/2023,1920,1921,1934,1916,"0,77K","-0,09%"
+9/8/2023,1922,1930,1936,1920,"0,72K","-0,46%"
+8/8/2023,1931,1942,1943,1928,"0,98K","-0,51%"
+7/8/2023,1941,1949,1952,1937,"0,51K","-0,32%"
+4/8/2023,1947,1941,1955,1928,"1,39K","0,36%"
+3/8/2023,1940,1943,1946,1937,"0,51K","-0,31%"
+2/8/2023,1946,1957,1963,1941,"0,74K","-0,19%"
+1/8/2023,1950,1974,1974,1950,"1,55K","-1,51%"
+31/07/2023,1980,1968,1981,1958,"0,62K","0,48%"
+28/07/2023,1970,1956,1972,1954,"3,24K","1,25%"
+27/07/2023,1946,1973,1983,1942,"194,25K","-1,24%"
+26/07/2023,1970,1966,1980,1963,"208,11K","0,33%"
+25/07/2023,1964,1957,1967,1952,"188,85K","0,08%"
+24/07/2023,1962,1964,1970,1955,"197,21K","-0,22%"
+21/07/2023,1967,1972,1976,1959,"156,54K","-0,22%"
+20/07/2023,1971,1980,1990,1968,"189,93K","-0,5%"
+19/07/2023,1981,1983,1985,1973,"159,41K",0.00%
+18/07/2023,1981,1958,1988,1958,"264,09K","1,25%"
+17/07/2023,1956,1959,1964,1949,"165,83K","-0,41%"
+14/07/2023,1964,1965,1968,1955,"209,31K","0,03%"
+13/07/2023,1964,1963,1969,1957,"241,22K","0,11%"
+12/7/2023,1962,1938,1965,1938,"270,87K","1,27%"
+11/7/2023,1937,1931,1945,1930,"189,37K","0,32%"
+10/7/2023,1931,1931,1934,1918,"208,09K","-0,08%"
+7/7/2023,1933,1917,1941,1915,"214,27K","0,89%"
+6/7/2023,1915,1922,1934,1909,"231,51K","-0,61%"
+5/7/2023,1927,1929,1943,1922,"245,93K",0.00%
+4/7/2023,1927,1929,1943,1922,"245,93K","-0,12%"
+3/7/2023,1930,1928,1940,1918,"152,96K","0,01%"
+30/06/2023,1929,1916,1931,1908,"180,69K","0,6%"
+29/06/2023,1918,1917,1921,1901,"205,25K","0,24%"
+28/06/2023,1913,1915,1917,1904,"0,63K","-0,09%"
+27/06/2023,1915,1927,1930,1912,"0,23K","-0,52%"
+26/06/2023,1925,1926,1935,1923,"0,77K","0,21%"
+23/06/2023,1921,1915,1939,1911,"0,75K","0,31%"
+22/06/2023,1915,1936,1936,1914,"0,37K","-1,09%"
+21/06/2023,1936,1940,1941,1922,"0,81K","-0,14%"
+20/06/2023,1939,1962,1962,1932,"0,74K","-0,45%"
+19/06/2023,1948,1971,1972,1941,"250,14K","-0,74%"
+16/06/2023,1962,1961,1971,1957,"0,62K","0,02%"
+15/06/2023,1962,1949,1964,1930,"0,82K","0,09%"
+14/06/2023,1960,1949,1965,1944,"1,07K","0,52%"
+13/06/2023,1950,1963,1976,1945,"0,76K","-0,56%"
+12/6/2023,1961,1966,1972,1955,"0,44K","-0,38%"
+9/6/2023,1968,1971,1978,1962,"0,43K","-0,08%"
+8/6/2023,1970,1949,1976,1948,"1,14K","1,03%"
+7/6/2023,1950,1971,1978,1947,"0,82K","-1,17%"
+6/6/2023,1973,1969,1974,1962,"0,34K","0,37%"
+5/6/2023,1966,1954,1971,1945,"1,70K","0,26%"
+2/6/2023,1961,1985,1991,1955,"1,02K","-1,3%"
+1/6/2023,1987,1972,1991,1961,"1,05K","0,68%"
+31/05/2023,1973,1968,1984,1963,"1,13K","0,25%"
+30/05/2023,1968,1952,1972,1941,"3,55K","-0,46%"
+29/05/2023,1977,1961,1982,1950,"264,37K","1,69%"
+26/05/2023,1944,1942,1957,1936,"166,04K","0,03%"
+25/05/2023,1944,1960,1965,1939,"253,88K","-1,06%"
+24/05/2023,1965,1977,1988,1958,"229,89K","-0,5%"
+23/05/2023,1975,1974,1980,1956,"214,36K","-0,14%"
+22/05/2023,1977,1979,1985,1971,"165,77K","-0,22%"
+19/05/2023,1982,1961,1987,1956,"234,60K","1,11%"
+18/05/2023,1960,1986,1989,1954,"227,73K","-1,26%"
+17/05/2023,1985,1993,1997,1978,"206,55K","-0,41%"
+16/05/2023,1993,2021,2023,1989,"229,94K","-1,47%"
+15/05/2023,2023,2013,2028,2011,"163,25K","0,14%"
+12/5/2023,2020,2021,2028,2006,"220,50K","-0,03%"
+11/5/2023,2021,2037,2048,2017,"296,98K","-0,81%"
+10/5/2023,2037,2042,2056,2028,"260,81K","-0,28%"
+9/5/2023,2043,2028,2045,2026,"199,70K","0,48%"
+8/5/2023,2033,2025,2037,2022,"182,21K","0,41%"
+5/5/2023,2025,2058,2061,2007,"283,30K","-1,5%"
+4/5/2023,2056,2055,2085,2039,"311,00K","0,92%"
+3/5/2023,2037,2026,2050,2016,"229,67K","0,68%"
+2/5/2023,2023,1991,2029,1987,"245,64K","1,56%"
+1/5/2023,1992,2000,2015,1986,"173,02K","-0,35%"
+28/04/2023,1999,1997,2004,1984,"172,45K","0,01%"
+27/04/2023,1999,2000,2013,1982,"203,90K","0,61%"
+26/04/2023,1987,2000,2010,1987,"0,62K","-0,41%"
+25/04/2023,1995,1995,2005,1979,"0,85K","0,23%"
+24/04/2023,1991,1983,1991,1975,"0,54K","0,47%"
+21/04/2023,1981,2005,2007,1973,"0,62K","-1,42%"
+20/04/2023,2010,1997,2015,1994,"0,42K","0,59%"
+19/04/2023,1998,2009,2010,1972,"0,92K","-0,61%"
+18/04/2023,2010,1997,2013,1995,"0,22K","0,64%"
+17/04/2023,1998,2005,2018,1985,"0,74K","-0,44%"
+14/04/2023,2007,2045,2052,1997,"1,48K","-1,92%"
+13/04/2023,2046,2020,2053,2020,"0,93K","1,49%"
+12/4/2023,2016,2010,2034,2007,"0,83K","0,28%"
+11/4/2023,2010,1997,2013,1996,"0,46K","0,76%"
+10/4/2023,1995,2004,2011,1988,"1,00K","-1,12%"
+6/4/2023,2017,2028,2029,2008,"1,20K","-0,46%"
+5/4/2023,2027,2030,2040,2019,"1,17K","-0,13%"
+4/4/2023,2029,1993,2034,1986,"1,09K","1,91%"
+3/4/2023,1991,1983,1999,1957,"0,76K","0,72%"
+31/03/2023,1977,1989,1996,1975,"0,75K","-0,58%"
+30/03/2023,1989,1973,1993,1963,"1,19K","1,1%"
+29/03/2023,1967,1975,1976,1960,"88,56K","-0,33%"
+28/03/2023,1974,1958,1977,1950,"183,58K","1,01%"
+27/03/2023,1954,1983,1984,1945,"206,63K","-1,51%"
+24/03/2023,1984,1996,2007,1978,"285,44K","-0,61%"
+23/03/2023,1996,1974,2006,1967,"262,25K","2,37%"
+22/03/2023,1950,1944,1982,1937,"245,03K","0,44%"
+21/03/2023,1941,1983,1989,1939,"248,93K","-2,1%"
+20/03/2023,1983,1990,2015,1970,"338,02K","0,47%"
+17/03/2023,1974,1926,1994,1922,"351,09K","2,63%"
+16/03/2023,1923,1923,1938,1912,"248,08K","-0,43%"
+15/03/2023,1931,1908,1943,1890,"385,45K","1,07%"
+14/03/2023,1911,1919,1919,1900,"261,28K","-0,29%"
+13/03/2023,1917,1877,1920,1876,"452,33K","2,64%"
+10/3/2023,1867,1835,1874,1830,"345,81K","1,78%"
+9/3/2023,1835,1818,1839,1815,"228,47K","0,88%"
+8/3/2023,1819,1818,1829,1813,"208,29K","-0,08%"
+7/3/2023,1820,1853,1857,1817,"248,23K","-1,87%"
+6/3/2023,1855,1861,1864,1851,"136,22K",0.00%
+3/3/2023,1855,1842,1864,1842,"158,96K","0,77%"
+2/3/2023,1841,1844,1845,1836,"139,76K","-0,27%"
+1/3/2023,1845,1834,1853,1830,"182,58K","0,47%"
+28/02/2023,1837,1824,1839,1811,"184,51K","0,65%"
+27/02/2023,1825,1818,1827,1812,"130,43K","0,87%"
+24/02/2023,1809,1825,1827,1809,"0,40K","-0,53%"
+23/02/2023,1819,1824,1833,1818,"0,65K","-0,79%"
+22/02/2023,1833,1837,1846,1825,"0,57K","-0,05%"
+21/02/2023,1834,1842,1848,1831,"0,91K","-0,45%"
+20/02/2023,1843,1851,1856,1839,"210,17K","0,03%"
+17/02/2023,1842,1836,1845,1820,"0,73K","-0,08%"
+16/02/2023,1843,1839,1846,1828,"0,65K","0,35%"
+15/02/2023,1837,1856,1862,1832,"0,78K","-1,08%"
+14/02/2023,1857,1856,1871,1845,"0,72K","0,1%"
+13/02/2023,1855,1867,1869,1853,"0,83K","-0,58%"
+10/2/2023,1866,1865,1873,1855,"0,77K","-0,22%"
+9/2/2023,1870,1879,1894,1862,"0,85K","-0,65%"
+8/2/2023,1882,1877,1890,1874,"1,03K","0,3%"
+7/2/2023,1877,1872,1889,1869,"1,45K","0,28%"
+6/2/2023,1871,1867,1885,1866,"1,59K","0,16%"
+3/2/2023,1868,1918,1924,1866,"2,60K","-2,8%"
+2/2/2023,1922,1959,1966,1917,"1,87K","-0,63%"
+1/2/2023,1934,1935,1962,1928,"2,19K","-0,12%"
+31/01/2023,1937,1930,1938,1907,"1,81K","0,33%"
+30/01/2023,1930,1936,1941,1927,"2,80K","0,04%"
+27/01/2023,1929,1929,1935,1917,"150,90K","-0,03%"
+26/01/2023,1930,1948,1950,1918,"223,26K","-0,65%"
+25/01/2023,1943,1939,1950,1921,"190,30K","0,37%"
+24/01/2023,1935,1932,1944,1918,"201,71K","0,35%"
+23/01/2023,1929,1928,1937,1913,"190,09K","0,02%"
+20/01/2023,1928,1934,1939,1922,"165,27K","0,22%"
+19/01/2023,1924,1907,1937,1902,"214,25K","0,89%"
+18/01/2023,1907,1911,1930,1899,"218,97K","-0,15%"
+17/01/2023,1910,1924,1932,1906,"268,37K",0.00%
+16/01/2023,1910,1924,1932,1906,"268,37K","-0,61%"
+13/01/2023,1922,1899,1925,1895,"247,88K","1,21%"
+12/1/2023,1899,1880,1907,1872,"265,17K","1,06%"
+11/1/2023,1879,1881,1891,1871,"222,25K","0,13%"
+10/1/2023,1877,1876,1885,1872,"170,51K","-0,07%"
+9/1/2023,1878,1873,1886,1869,"204,55K","0,43%"
+6/1/2023,1870,1836,1875,1835,"215,37K","1,58%"
+5/1/2023,1841,1861,1864,1830,"188,60K","-0,99%"
+4/1/2023,1859,1845,1871,1842,"198,35K","0,7%"
+3/1/2023,1846,1832,1857,1831,"212,27K","1,09%"
+30/12/2022,1826,1822,1832,1820,"107,50K","0,01%"
+29/12/2022,1826,1812,1827,1811,"105,99K","0,95%"
+28/12/2022,1809,1812,1812,1801,"0,43K","-0,41%"
+27/12/2022,1816,1800,1834,1800,"0,22K","1,05%"
+23/12/2022,1797,1794,1806,1793,"0,24K","0,5%"
+22/12/2022,1789,1818,1822,1787,"0,41K","-1,65%"
+21/12/2022,1819,1822,1825,1816,"0,16K","-0,01%"
+20/12/2022,1819,1796,1824,1790,"0,51K","1,54%"
+19/12/2022,1791,1795,1801,1789,"0,21K","-0,14%"
+16/12/2022,1794,1780,1797,1779,"0,43K","0,72%"
+15/12/2022,1781,1812,1812,1775,"0,69K","-1,71%"
+14/12/2022,1812,1815,1817,1800,"0,28K","-0,37%"
+13/12/2022,1818,1786,1829,1785,"0,57K","1,87%"
+12/12/2022,1785,1802,1802,1782,"0,31K","-1,03%"
+9/12/2022,1804,1794,1811,1794,"0,50K","0,52%"
+8/12/2022,1794,1793,1799,1787,"0,56K","0,18%"
+7/12/2022,1791,1775,1796,1774,"0,84K","0,87%"
+6/12/2022,1776,1775,1786,1773,"0,55K","0,07%"
+5/12/2022,1774,1804,1815,1772,"1,34K","-1,57%"
+2/12/2022,1803,1810,1812,1786,"1,17K","-0,31%"
+1/12/2022,1808,1778,1811,1778,"1,27K","3,14%"
+30/11/2022,1753,1756,1777,1752,"1,56K","-0,18%"
+29/11/2022,1756,1748,1765,1746,"1,59K","0,92%"
+28/11/2022,1740,1755,1764,1738,"132,77K","-0,78%"
+25/11/2022,1754,1751,1761,1746,"134,30K",0.00%
+24/11/2022,1754,1751,1761,1746,"134,30K","0,48%"
+23/11/2022,1746,1741,1755,1719,"167,77K","0,33%"
+22/11/2022,1740,1740,1751,1738,"153,09K","0,02%"
+21/11/2022,1740,1752,1755,1734,"166,08K","-0,84%"
+18/11/2022,1754,1763,1770,1749,"137,33K","-0,49%"
+17/11/2022,1763,1777,1778,1757,"169,10K","-0,72%"
+16/11/2022,1776,1782,1788,1773,"200,76K","-0,06%"
+15/11/2022,1777,1774,1792,1770,"283,02K","-0,01%"
+14/11/2022,1777,1769,1778,1756,"191,35K","0,42%"
+11/11/2022,1769,1758,1776,1750,"227,04K","0,9%"
+10/11/2022,1754,1710,1761,1706,"305,72K","2,33%"
+9/11/2022,1714,1715,1726,1705,"239,65K","-0,13%"
+8/11/2022,1716,1678,1720,1667,"297,62K","2,11%"
+7/11/2022,1681,1679,1686,1670,"187,59K","0,23%"
+4/11/2022,1677,1632,1686,1631,"293,52K","2,8%"
+3/11/2022,1631,1639,1643,1618,"254,70K","-1,16%"
+2/11/2022,1650,1651,1673,1637,"220,93K","0,02%"
+1/11/2022,1650,1636,1660,1634,"197,98K","0,55%"
+31/10/2022,1641,1647,1649,1635,"128,41K","-0,25%"
+28/10/2022,1645,1667,1671,1641,"196,36K","-0,93%"
+27/10/2022,1660,1664,1669,1654,"2,30K","-0,25%"
+26/10/2022,1664,1652,1674,1652,"0,32K","0,67%"
+25/10/2022,1653,1650,1661,1637,"0,59K","0,25%"
+24/10/2022,1649,1662,1666,1644,"0,15K","-0,14%"
+21/10/2022,1652,1626,1657,1618,"0,64K","1,21%"
+20/10/2022,1632,1629,1644,1621,"0,50K","0,17%"
+19/10/2022,1629,1652,1654,1628,"0,30K","-1,31%"
+18/10/2022,1651,1651,1660,1647,"0,72K","-0,49%"
+17/10/2022,1659,1646,1668,1645,"0,60K","0,92%"
+14/10/2022,1644,1666,1672,1641,"0,64K","-1,68%"
+13/10/2022,1672,1675,1680,1645,"0,32K","-0,03%"
+12/10/2022,1672,1668,1680,1663,"0,23K","-0,51%"
+11/10/2022,1681,1670,1686,1665,"0,74K","0,65%"
+10/10/2022,1670,1699,1701,1668,"0,49K","-1,99%"
+7/10/2022,1704,1714,1715,1694,"0,26K","-0,67%"
+6/10/2022,1716,1719,1729,1710,"0,23K","-0,01%"
+5/10/2022,1716,1729,1730,1704,"1,04K","-0,57%"
+4/10/2022,1726,1703,1732,1700,"0,81K","1,67%"
+3/10/2022,1697,1668,1704,1664,"0,64K","1,8%"
+30/09/2022,1667,1665,1679,1663,"0,39K","0,22%"
+29/09/2022,1664,1662,1668,1645,"2,39K","0,2%"
+28/09/2022,1660,1627,1662,1613,"18,31K","2,08%"
+27/09/2022,1627,1622,1640,1621,"15,91K","0,18%"
+26/09/2022,1624,1643,1646,1618,"14,96K","-1,32%"
+23/09/2022,1645,1670,1675,1636,"17,01K","-1,56%"
+22/09/2022,1671,1670,1684,1654,"6,42K","0,34%"
+21/09/2022,1666,1665,1687,1652,"10,10K","0,29%"
+20/09/2022,1661,1675,1678,1658,"7,07K","-0,4%"
+19/09/2022,1668,1673,1678,1657,"6,29K","-0,31%"
+16/09/2022,1673,1663,1679,1652,"10,86K","0,36%"
+15/09/2022,1667,1697,1697,1659,"12,32K","-1,85%"
+14/09/2022,1698,1703,1707,1693,"7,08K","-0,52%"
+13/09/2022,1707,1726,1733,1697,"11,55K","-1,37%"
+12/9/2022,1731,1719,1736,1713,"5,71K","0,7%"
+9/9/2022,1719,1710,1731,1710,"8,17K","0,48%"
+8/9/2022,1711,1720,1729,1704,"5,09K","-0,44%"
+7/9/2022,1718,1703,1721,1693,"7,51K","0,87%"
+6/9/2022,1703,1715,1727,1701,"7,57K","-0,55%"
+5/9/2022,1713,1724,1737,1711,"206,27K","-0,01%"
+2/9/2022,1713,1699,1720,1697,"8,55K","0,79%"
+1/9/2022,1700,1713,1713,1690,"11,25K","-1,01%"
+31/08/2022,1717,1726,1729,1712,"8,91K","-0,58%"
+30/08/2022,1727,1741,1743,1724,"6,95K","-0,56%"
+29/08/2022,1737,1736,1741,1718,"0,95K","0,01%"
+26/08/2022,1737,1758,1758,1733,"1,05K","-1,21%"
+25/08/2022,1758,1751,1765,1750,"0,73K","0,57%"
+24/08/2022,1748,1746,1755,1742,"0,97K","0,03%"
+23/08/2022,1747,1735,1753,1730,"1,57K","0,74%"
+22/08/2022,1734,1747,1747,1726,"0,68K","-0,8%"
+19/08/2022,1748,1758,1758,1745,"0,62K","-0,46%"
+18/08/2022,1757,1763,1771,1755,"0,71K","-0,31%"
+17/08/2022,1762,1776,1782,1759,"0,62K","-0,73%"
+16/08/2022,1775,1780,1783,1771,"0,43K","-0,47%"
+15/08/2022,1783,1804,1804,1773,"0,66K","-0,97%"
+12/8/2022,1801,1789,1804,1786,"0,57K","0,49%"
+11/8/2022,1792,1792,1799,1784,"1,92K","-0,36%"
+10/8/2022,1799,1796,1809,1788,"1,60K","0,09%"
+9/8/2022,1797,1790,1801,1784,"0,93K","0,4%"
+8/8/2022,1790,1776,1790,1772,"1,69K","0,78%"
+5/8/2022,1776,1791,1795,1765,"2,04K","-0,86%"
+4/8/2022,1791,1766,1796,1764,"1,65K","1,72%"
+3/8/2022,1761,1763,1774,1755,"1,82K","-0,78%"
+2/8/2022,1775,1774,1791,1762,"2,47K","0,12%"
+1/8/2022,1773,1768,1777,1760,"1,07K","0,33%"
+29/07/2022,1767,1759,1770,1754,"0,86K","0,71%"
+28/07/2022,1754,1737,1759,1737,"1,47K","2,05%"
+27/07/2022,1719,1715,1740,1709,"144,87K","0,08%"
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+20/05/2022,1842,1840,1848,1831,"143,05K","0,05%"
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+5/5/2022,1876,1884,1911,1872,"218,39K","0,37%"
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+27/04/2022,1886,1903,1903,1879,"1,79K","-0,83%"
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+13/04/2022,1982,1969,1982,1964,"0,53K","0,44%"
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+11/4/2022,1945,1950,1971,1941,"0,40K","0,14%"
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+5/4/2022,1924,1934,1945,1918,"1,19K","-0,34%"
+4/4/2022,1931,1925,1938,1918,"2,01K","0,5%"
+1/4/2022,1921,1939,1941,1919,"1,09K","-1,55%"
+31/03/2022,1951,1935,1952,1922,"1,46K","0,77%"
+30/03/2022,1936,1922,1940,1918,"2,38K","1,25%"
+29/03/2022,1912,1922,1929,1888,"128,05K","-1,42%"
+28/03/2022,1940,1959,1960,1916,"181,37K","-0,74%"
+25/03/2022,1954,1958,1965,1943,"147,90K","-0,41%"
+24/03/2022,1962,1944,1967,1937,"181,20K","1,29%"
+23/03/2022,1937,1921,1949,1916,"153,31K","0,82%"
+22/03/2022,1922,1936,1940,1910,"153,28K","-0,41%"
+21/03/2022,1930,1922,1942,1917,"146,41K","0,01%"
+18/03/2022,1929,1944,1946,1918,"150,88K","-0,72%"
+17/03/2022,1943,1928,1951,1924,"149,83K","1,78%"
+16/03/2022,1909,1920,1930,1895,"195,46K","-1,06%"
+15/03/2022,1930,1954,1957,1908,"220,37K","-1,59%"
+14/03/2022,1961,1989,1995,1952,"162,20K","-1,22%"
+11/3/2022,1985,2000,2004,1961,"262,09K","-0,77%"
+10/3/2022,2000,1993,2015,1975,"303,27K","0,61%"
+9/3/2022,1988,2060,2069,1981,"360,35K","-2,7%"
+8/3/2022,2043,2001,2079,1986,"447,65K","2,37%"
+7/3/2022,1996,1979,2008,1964,"372,19K","1,49%"
+4/3/2022,1967,1939,1975,1932,"241,53K","1,59%"
+3/3/2022,1936,1932,1945,1923,"180,21K","0,71%"
+2/3/2022,1922,1945,1951,1916,"227,98K","-1,11%"
+1/3/2022,1944,1908,1953,1903,"224,00K","2,27%"
+28/02/2022,1901,1921,1935,1892,"249,27K","0,69%"
+25/02/2022,1888,1907,1925,1884,"229,78K","-1,96%"
+24/02/2022,1925,1911,1975,1880,"2,71K","0,84%"
+23/02/2022,1909,1900,1912,1890,"1,98K","0,16%"
+22/02/2022,1906,1903,1917,1889,"2,19K","-0,05%"
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+8/2/2022,1827,1821,1829,1816,"0,93K","0,33%"
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+26/01/2022,1830,1848,1850,1814,"270,03K","-1,23%"
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+21/01/2022,1832,1841,1844,1828,"225,25K","-0,59%"
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+17/01/2022,1812,1819,1823,1805,"362,94K","-0,23%"
+14/01/2022,1817,1822,1829,1814,"174,94K","-0,27%"
+13/01/2022,1821,1826,1828,1812,"215,52K","-0,32%"
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+3/1/2022,1800,1830,1833,1798,"168,31K","-1,56%"

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8318d2d632e7c1afb53ed2eea2d61dcab5160a6c476b5904969b65bf31c5bfeb
+size 977

requirements.txt

@@ -0,0 +1,7 @@
+Flask==2.3.3
+pandas==2.0.3
+numpy==1.24.3
+scikit-learn==1.3.0
+matplotlib==3.7.2
+seaborn==0.12.2
+Werkzeug==2.3.7

scaler.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:979f0bc38f3c9923f8e433575b8d161ff21fa37d8a00932c41f847263dadfba1
+size 561

templates/data_analysis.html

@@ -0,0 +1,208 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Data Analysis - Gold Price Prediction</title>
+    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
+    <style>
+        .gradient-bg {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+        }
+        .gold-accent {
+            color: #FFD700;
+        }
+        .stat-card {
+            border: none;
+            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+            transition: transform 0.3s ease;
+        }
+        .stat-card:hover {
+            transform: translateY(-5px);
+        }
+        .navbar-brand {
+            font-weight: bold;
+        }
+    </style>
+</head>
+<body>
+    <!-- Navigation -->
+    <nav class="navbar navbar-expand-lg navbar-dark gradient-bg">
+        <div class="container">
+            <a class="navbar-brand" href="/">
+                <i class="fas fa-coins gold-accent"></i>
+                Gold Price Predictor
+            </a>
+            <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav">
+                <span class="navbar-toggler-icon"></span>
+            </button>
+            <div class="collapse navbar-collapse" id="navbarNav">
+                <ul class="navbar-nav ms-auto">
+                    <li class="nav-item">
+                        <a class="nav-link" href="/">Home</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link active" href="/data-analysis">Data Analysis</a>
+                    </li>
+                </ul>
+            </div>
+        </div>
+    </nav>
+
+    <!-- Main Content -->
+    <div class="container my-5">
+        <div class="row mb-4">
+            <div class="col-12">
+                <h1 class="text-center mb-5">
+                    <i class="fas fa-chart-bar text-warning"></i>
+                    Analisis Data Historis Harga Emas
+                </h1>
+            </div>
+        </div>
+
+        <!-- Statistics Cards -->
+        <div class="row mb-5">
+            <div class="col-md-3 mb-3">
+                <div class="card stat-card text-center">
+                    <div class="card-body">
+                        <i class="fas fa-database fa-2x text-primary mb-3"></i>
+                        <h5 class="card-title">Total Records</h5>
+                        <h3 class="text-primary">{{ stats.total_records }}</h3>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-3 mb-3">
+                <div class="card stat-card text-center">
+                    <div class="card-body">
+                        <i class="fas fa-calendar-alt fa-2x text-info mb-3"></i>
+                        <h5 class="card-title">Date Range</h5>
+                        <p class="text-info small">{{ stats.date_range }}</p>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-3 mb-3">
+                <div class="card stat-card text-center">
+                    <div class="card-body">
+                        <i class="fas fa-chart-line fa-2x text-success mb-3"></i>
+                        <h5 class="card-title">Avg Close Price</h5>
+                        <h4 class="text-success">IDR {{ "{:,.0f}".format(stats.avg_close) }}</h4>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-3 mb-3">
+                <div class="card stat-card text-center">
+                    <div class="card-body">
+                        <i class="fas fa-chart-area fa-2x text-warning mb-3"></i>
+                        <h5 class="card-title">Avg Open Price</h5>
+                        <h4 class="text-warning">IDR {{ "{:,.0f}".format(stats.avg_open) }}</h4>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- Additional Statistics -->
+        <div class="row mb-5">
+            <div class="col-md-4 mb-3">
+                <div class="card stat-card">
+                    <div class="card-body text-center">
+                        <i class="fas fa-arrow-down fa-2x text-danger mb-3"></i>
+                        <h5 class="card-title">Minimum Close Price</h5>
+                        <h4 class="text-danger">IDR {{ "{:,.0f}".format(stats.min_close) }}</h4>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-4 mb-3">
+                <div class="card stat-card">
+                    <div class="card-body text-center">
+                        <i class="fas fa-arrow-up fa-2x text-success mb-3"></i>
+                        <h5 class="card-title">Maximum Close Price</h5>
+                        <h4 class="text-success">IDR {{ "{:,.0f}".format(stats.max_close) }}</h4>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-4 mb-3">
+                <div class="card stat-card">
+                    <div class="card-body text-center">
+                        <i class="fas fa-clock fa-2x text-primary mb-3"></i>
+                        <h5 class="card-title">Current Price</h5>
+                        <h5 class="text-primary">Close: IDR {{ "{:,.0f}".format(stats.current_close) }}</h5>
+                        <h5 class="text-info">Open: IDR {{ "{:,.0f}".format(stats.current_open) }}</h5>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- Historical Chart -->
+        <div class="card stat-card mb-5">
+            <div class="card-header">
+                <h5 class="mb-0">
+                    <i class="fas fa-chart-line"></i>
+                    Grafik Harga Historis Emas
+                </h5>
+            </div>
+            <div class="card-body text-center">
+                <img src="data:image/png;base64,{{ chart }}" class="img-fluid" alt="Historical Price Chart">
+            </div>
+        </div>
+
+        <!-- Information Cards -->
+        <div class="row">
+            <div class="col-md-6 mb-4">
+                <div class="card stat-card">
+                    <div class="card-header">
+                        <h5 class="mb-0">
+                            <i class="fas fa-info-circle"></i>
+                            Tentang Data
+                        </h5>
+                    </div>
+                    <div class="card-body">
+                        <ul class="list-unstyled">
+                            <li><i class="fas fa-check text-success"></i> Data diperoleh dari API Pluang</li>
+                            <li><i class="fas fa-check text-success"></i> Mencakup data historis emas selama 5 tahun</li>
+                            <li><i class="fas fa-check text-success"></i> Data telah dibersihkan dan dinormalisasi</li>
+                            <li><i class="fas fa-check text-success"></i> Tidak ada data yang hilang (null values)</li>
+                        </ul>
+                    </div>
+                </div>
+            </div>
+            <div class="col-md-6 mb-4">
+                <div class="card stat-card">
+                    <div class="card-header">
+                        <h5 class="mb-0">
+                            <i class="fas fa-cog"></i>
+                            Tentang Model
+                        </h5>
+                    </div>
+                    <div class="card-body">
+                        <ul class="list-unstyled">
+                            <li><i class="fas fa-check text-success"></i> Algoritma: Linear Regression</li>
+                            <li><i class="fas fa-check text-success"></i> Sliding Window: 7 hari</li>
+                            <li><i class="fas fa-check text-success"></i> Normalisasi: MinMaxScaler</li>
+                            <li><i class="fas fa-check text-success"></i> Train/Test Split: 80/20</li>
+                        </ul>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- Back to Prediction -->
+        <div class="text-center mt-5">
+            <a href="/" class="btn btn-warning btn-lg">
+                <i class="fas fa-arrow-left"></i>
+                Kembali ke Prediksi
+            </a>
+        </div>
+    </div>
+
+    <!-- Footer -->
+    <footer class="gradient-bg text-center py-4 mt-5">
+        <div class="container">
+            <p class="mb-0">&copy; 2025 Kelompok 4 - Sistem Prediksi Harga Emas. Powered by Machine Learning.</p>
+        </div>
+    </footer>
+
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
+</body>
+</html>

templates/error.html

@@ -0,0 +1,61 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Error - Gold Price Prediction</title>
+    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
+    <style>
+        .gradient-bg {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+        }
+        .gold-accent {
+            color: #FFD700;
+        }
+        .navbar-brand {
+            font-weight: bold;
+        }
+    </style>
+</head>
+<body>
+    <!-- Navigation -->
+    <nav class="navbar navbar-expand-lg navbar-dark gradient-bg">
+        <div class="container">
+            <a class="navbar-brand" href="/">
+                <i class="fas fa-coins gold-accent"></i>
+                Gold Price Predictor
+            </a>
+        </div>
+    </nav>
+
+    <!-- Error Content -->
+    <div class="container my-5">
+        <div class="row justify-content-center">
+            <div class="col-md-8 text-center">
+                <div class="alert alert-danger" role="alert">
+                    <i class="fas fa-exclamation-triangle fa-3x mb-3"></i>
+                    <h4 class="alert-heading">Oops! Terjadi Kesalahan</h4>
+                    <p>{{ error }}</p>
+                    <hr>
+                    <p class="mb-0">
+                        <a href="/" class="btn btn-primary">
+                            <i class="fas fa-home"></i> Kembali ke Beranda
+                        </a>
+                    </p>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <!-- Footer -->
+    <footer class="gradient-bg text-center py-4 mt-5 fixed-bottom">
+        <div class="container">
+            <p class="mb-0">&copy; 2025 Kelompok 4 - Sistem Prediksi Harga Emas.</p>
+        </div>
+    </footer>
+
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
+</body>
+</html>

templates/index.html

@@ -0,0 +1,258 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Gold Price Prediction System</title>
+    <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
+    <style>
+        .gradient-bg {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+        }
+        .gold-accent {
+            color: #FFD700;
+        }
+        .prediction-card {
+            border: none;
+            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+            transition: transform 0.3s ease;
+        }
+        .prediction-card:hover {
+            transform: translateY(-5px);
+        }
+        .price-up {
+            color: #28a745;
+        }
+        .price-down {
+            color: #dc3545;
+        }
+        .loading-spinner {
+            display: none;
+        }
+        .navbar-brand {
+            font-weight: bold;
+        }
+        .hero-section {
+            background: linear-gradient(rgba(0,0,0,0.5), rgba(0,0,0,0.5)), url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1000 300"><defs><linearGradient id="grad" x1="0%" y1="0%" x2="100%" y2="100%"><stop offset="0%" style="stop-color:%23FFD700;stop-opacity:0.3" /><stop offset="100%" style="stop-color:%23FFA500;stop-opacity:0.1" /></linearGradient></defs><rect width="1000" height="300" fill="url(%23grad)"/></svg>');
+            color: white;
+            padding: 100px 0;
+        }
+    </style>
+</head>
+<body>
+    <!-- Navigation -->
+    <nav class="navbar navbar-expand-lg navbar-dark gradient-bg">
+        <div class="container">
+            <a class="navbar-brand" href="#">
+                <i class="fas fa-coins gold-accent"></i>
+                Gold Price Predictor
+            </a>
+            <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbarNav">
+                <span class="navbar-toggler-icon"></span>
+            </button>
+            <div class="collapse navbar-collapse" id="navbarNav">
+                <ul class="navbar-nav ms-auto">
+                    <li class="nav-item">
+                        <a class="nav-link active" href="/">Home</a>
+                    </li>
+                    <li class="nav-item">
+                        <a class="nav-link" href="/data-analysis">Data Analysis</a>
+                    </li>
+                </ul>
+            </div>
+        </div>
+    </nav>
+
+    <!-- Hero Section -->
+    <section class="hero-section text-center">
+        <div class="container">
+            <h1 class="display-4 mb-4">
+                <i class="fas fa-chart-line gold-accent"></i>
+                Prediksi Harga Emas 7 Hari Kedepan
+            </h1>
+            <p class="lead mb-5">Sistem prediksi harga emas menggunakan Machine Learning dengan Linear Regression</p>
+            <button class="btn btn-warning btn-lg" onclick="predictGoldPrice()">
+                <i class="fas fa-magic"></i> Prediksi Sekarang
+            </button>
+        </div>
+    </section>
+
+    <!-- Main Content -->
+    <div class="container my-5">
+        <!-- Loading Spinner -->
+        <div class="text-center loading-spinner" id="loadingSpinner">
+            <div class="spinner-border text-warning" role="status" style="width: 3rem; height: 3rem;">
+                <span class="visually-hidden">Loading...</span>
+            </div>
+            <p class="mt-3">Menganalisis data dan membuat prediksi...</p>
+        </div>
+
+        <!-- Results Section -->
+        <div id="resultsSection" style="display: none;">
+            <!-- Current Prices -->
+            <div class="row mb-4">
+                <div class="col-md-6">
+                    <div class="card prediction-card text-center">
+                        <div class="card-body">
+                            <h5 class="card-title"><i class="fas fa-clock"></i> Harga Saat Ini</h5>
+                            <div id="currentPrices"></div>
+                        </div>
+                    </div>
+                </div>
+                <div class="col-md-6">
+                    <div class="card prediction-card text-center">
+                        <div class="card-body">
+                            <h5 class="card-title"><i class="fas fa-trending-up"></i> Perkiraan Perubahan Total</h5>
+                            <div id="totalChanges"></div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <!-- Prediction Chart -->
+            <div class="card prediction-card mb-4">
+                <div class="card-header">
+                    <h5 class="mb-0"><i class="fas fa-chart-area"></i> Grafik Prediksi Harga Emas</h5>
+                </div>
+                <div class="card-body text-center">
+                    <img id="predictionChart" class="img-fluid" alt="Prediction Chart">
+                </div>
+            </div>
+
+            <!-- Predictions Table -->
+            <div class="card prediction-card">
+                <div class="card-header">
+                    <h5 class="mb-0"><i class="fas fa-table"></i> Prediksi Harga 7 Hari Kedepan</h5>
+                </div>
+                <div class="card-body">
+                    <div class="table-responsive">
+                        <table class="table table-striped table-hover">
+                            <thead class="table-dark">
+                                <tr>
+                                    <th>Tanggal</th>
+                                    <th>Harga Tutup (IDR)</th>
+                                    <th>Perubahan Tutup (%)</th>
+                                    <th>Harga Buka (IDR)</th>
+                                    <th>Perubahan Buka (%)</th>
+                                </tr>
+                            </thead>
+                            <tbody id="predictionsTable">
+                            </tbody>
+                        </table>
+                    </div>
+                </div>
+            </div>
+        </div>
+
+        <!-- Error Section -->
+        <div id="errorSection" style="display: none;">
+            <div class="alert alert-danger text-center" role="alert">
+                <i class="fas fa-exclamation-triangle"></i>
+                <span id="errorMessage"></span>
+            </div>
+        </div>
+    </div>
+
+    <!-- Footer -->
+    <footer class="gradient-bg text-center py-4 mt-5">
+        <div class="container">
+            <p class="mb-0">&copy; 2025 Kelompok 4 - Sistem Prediksi Harga Emas. Powered by Machine Learning.</p>
+        </div>
+    </footer>
+
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
+    <script>
+        function predictGoldPrice() {
+            // Show loading spinner
+            document.getElementById('loadingSpinner').style.display = 'block';
+            document.getElementById('resultsSection').style.display = 'none';
+            document.getElementById('errorSection').style.display = 'none';
+
+            // Make API call
+            fetch('/predict', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                }
+            })
+            .then(response => response.json())
+            .then(data => {
+                document.getElementById('loadingSpinner').style.display = 'none';
+                
+                if (data.success) {
+                    displayResults(data);
+                } else {
+                    displayError(data.error || 'Unknown error occurred');
+                }
+            })
+            .catch(error => {
+                document.getElementById('loadingSpinner').style.display = 'none';
+                displayError('Network error: ' + error.message);
+            });
+        }
+
+        function displayResults(data) {
+            // Display current prices
+            const currentPricesHtml = `
+                <p class="mb-1"><strong>Harga Tutup:</strong> <span class="gold-accent">IDR ${data.current_prices.close.toLocaleString()}</span></p>
+                <p class="mb-0"><strong>Harga Buka:</strong> <span class="gold-accent">IDR ${data.current_prices.open.toLocaleString()}</span></p>
+            `;
+            document.getElementById('currentPrices').innerHTML = currentPricesHtml;
+
+            // Display total changes
+            const totalChangesHtml = `
+                <p class="mb-1"><strong>Tutup:</strong> 
+                    <span class="${data.total_changes.close >= 0 ? 'price-up' : 'price-down'}">
+                        ${data.total_changes.close >= 0 ? '+' : ''}${data.total_changes.close}%
+                        <i class="fas fa-arrow-${data.total_changes.close >= 0 ? 'up' : 'down'}"></i>
+                    </span>
+                </p>
+                <p class="mb-0"><strong>Buka:</strong> 
+                    <span class="${data.total_changes.open >= 0 ? 'price-up' : 'price-down'}">
+                        ${data.total_changes.open >= 0 ? '+' : ''}${data.total_changes.open}%
+                        <i class="fas fa-arrow-${data.total_changes.open >= 0 ? 'up' : 'down'}"></i>
+                    </span>
+                </p>
+            `;
+            document.getElementById('totalChanges').innerHTML = totalChangesHtml;
+
+            // Display chart
+            document.getElementById('predictionChart').src = 'data:image/png;base64,' + data.chart;
+
+            // Display predictions table
+            let tableHtml = '';
+            data.predictions.forEach(prediction => {
+                tableHtml += `
+                    <tr>
+                        <td><strong>${prediction.date}</strong></td>
+                        <td>IDR ${prediction.close_price.toLocaleString()}</td>
+                        <td class="${prediction.close_change >= 0 ? 'price-up' : 'price-down'}">
+                            ${prediction.close_change >= 0 ? '+' : ''}${prediction.close_change}%
+                            <i class="fas fa-arrow-${prediction.close_change >= 0 ? 'up' : 'down'}"></i>
+                        </td>
+                        <td>IDR ${prediction.open_price.toLocaleString()}</td>
+                        <td class="${prediction.open_change >= 0 ? 'price-up' : 'price-down'}">
+                            ${prediction.open_change >= 0 ? '+' : ''}${prediction.open_change}%
+                            <i class="fas fa-arrow-${prediction.open_change >= 0 ? 'up' : 'down'}"></i>
+                        </td>
+                    </tr>
+                `;
+            });
+            document.getElementById('predictionsTable').innerHTML = tableHtml;
+
+            document.getElementById('resultsSection').style.display = 'block';
+        }
+
+        function displayError(errorMessage) {
+            document.getElementById('errorMessage').textContent = errorMessage;
+            document.getElementById('errorSection').style.display = 'block';
+        }
+
+        function formatNumber(num) {
+            return new Intl.NumberFormat('id-ID').format(num);
+        }
+    </script>
+</body>
+</html>