Update app.py

app.py

@@ -19,21 +19,21 @@ with open('scaler.pkl', 'rb') as scaler_file:
 def predict_7_days(sell_features, buy_features, linear_model, scaler):
     # Data dari frontend
     # Ambil nilai input (pastikan semuanya adalah angka)
-    sell_1 = float(sell_features[7])
-    sell_2 = float(sell_features[6])
-    sell_3 = float(sell_features[5])
-    sell_4 = float(sell_features[4])
-    sell_5 = float(sell_features[3])
-    sell_6 = float(sell_features[2])
-    sell_7 = float(sell_features[1])
-
-    buy_1 = float(buy_features[7])
-    buy_2 = float(buy_features[6])
-    buy_3 = float(buy_features[5])
-    buy_4 = float(buy_features[4])
-    buy_5 = float(buy_features[3])
-    buy_6 = float(buy_features[2])
-    buy_7 = float(buy_features[1])
+    sell_1 = float(sell_features[6])
+    sell_2 = float(sell_features[5])
+    sell_3 = float(sell_features[4])
+    sell_4 = float(sell_features[3])
+    sell_5 = float(sell_features[2])
+    sell_6 = float(sell_features[1])
+    sell_7 = float(sell_features[0])
+
+    buy_1 = float(buy_features[6])
+    buy_2 = float(buy_features[5])
+    buy_3 = float(buy_features[4])
+    buy_4 = float(buy_features[3])
+    buy_5 = float(buy_features[2])
+    buy_6 = float(buy_features[1])
+    buy_7 = float(buy_features[0])
 
     # Menyusun data jual dan beli sebagai pasangan (sell, buy)
     data = np.array([
@@ -80,7 +80,7 @@ def predict_7_days(sell_features, buy_features, linear_model, scaler):
 
 
     # Harga terakhir
-    last_price = [sell_features[0], buy_features[0]]
+    last_price = [sell_features[7], buy_features[7]]
 
     # Hitung persentase perubahan harian
     predictions_df['sell_change'] = predictions_df['sell'].pct_change().fillna(0) * 100