Update app.py

app.py

@@ -1,69 +1,32 @@
 import streamlit as st
-import pandas as pd
-import numpy as np
 import yfinance as yf
+import pandas as pd
 import matplotlib.pyplot as plt
-from scipy.optimize import minimize
 
 # Fungsi untuk mengunduh data saham
 def get_stock_data(tickers, start, end):
     data = yf.download(tickers, start=start, end=end)
-    st.write("Data mentah yang diunduh:")
-    st.write(data.head())  # Menampilkan 5 baris pertama untuk debug
-    if 'Adj Close' in data.columns:
+    if data.empty:
+        st.error("Data saham tidak ditemukan. Periksa ticker atau tanggal.")
+        return None
+    elif 'Adj Close' in data.columns:
         return data['Adj Close']
+    elif 'Close' in data.columns:
+        return data['Close']
     else:
-        st.error("Kolom 'Adj Close' tidak ditemukan. Coba cek ticker atau tanggal.")
+        st.error("Kolom 'Adj Close' atau 'Close' tidak ditemukan.")
         return None
 
-# Fungsi untuk menghitung return harian
-def calculate_daily_returns(data):
-    return data.pct_change().dropna()
-
-# Fungsi untuk menghitung portofolio optimal dengan Model Markowitz
-def optimize_portfolio(returns):
-    num_assets = len(returns.columns)
-    weights = np.random.random(num_assets)
-    weights /= np.sum(weights)
-
-    def portfolio_performance(weights):
-        port_return = np.sum(returns.mean() * weights) * 252
-        port_volatility = np.sqrt(np.dot(weights.T, np.dot(returns.cov() * 252, weights)))
-        return port_volatility
-
-    constraints = ({'type': 'eq', 'fun': lambda x: np.sum(x) - 1})
-    bounds = tuple((0, 1) for _ in range(num_assets))
-    result = minimize(portfolio_performance, weights, method='SLSQP', bounds=bounds, constraints=constraints)
-    
-    return result.x
-
 # Streamlit UI
-st.title("Analisis Portofolio Saham Model Markowitz")
-
-# Input pengguna untuk daftar saham
-tickers = st.text_input("Masukkan kode saham (pisahkan dengan koma)", "BBCA.JK,TLKM.JK,UNVR.JK")
+st.title("Analisis Portofolio Saham")
+tickers_list = st.text_input("Masukkan ticker saham (contoh: BBCA.JK, TLKM.JK)", "BBCA.JK, TLKM.JK").split(",")
 start_date = st.date_input("Pilih tanggal mulai", pd.to_datetime("2020-01-01"))
 end_date = st.date_input("Pilih tanggal akhir", pd.to_datetime("2020-12-31"))
 
-if st.button("Analisis"):
-    tickers_list = [t.strip() for t in tickers.split(',')]
+if st.button("Dapatkan Data"):
     data = get_stock_data(tickers_list, start_date, end_date)
-    
-    if not data.empty:
-        st.write("Data Harga Saham")
-        st.line_chart(data)
-
-        returns = calculate_daily_returns(data)
-        optimal_weights = optimize_portfolio(returns)
-
-        st.write("Bobot Optimal Portofolio:")
-        for ticker, weight in zip(tickers_list, optimal_weights):
-            st.write(f"{ticker}: {weight:.2%}")
-
-        # Visualisasi Portofolio
-        fig, ax = plt.subplots()
-        ax.pie(optimal_weights, labels=tickers_list, autopct='%1.1f%%', startangle=90)
-        ax.axis("equal")
-        st.pyplot(fig)
-    else:
-        st.error("Gagal mengambil data saham. Pastikan kode saham benar.")
+    if data is not None:
+        st.write("Data Saham:")
+        st.write(data.tail())
+        # Plot harga saham
+        st.line_chart(data)