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# import library
import streamlit as st
import pandas as pd
import numpy as np
import pickle
# Load Model
with open('model.pkl', 'rb') as file:
model = pickle.load(file)
# Function untuk menjalankan streamlit model predictor
def run():
# Set judul
st.title("Memprediksi Kemungkinan Seseorang Mampu Membayar Kredit atau Tidak")
st.markdown('---')
st.image("https://dlabs.ai/wp-content/uploads/2021/09/price-prediction-1024x538.png")
# Buat Form Untuk Data Inference
st.markdown('## Input Data')
with st.form('my_form'):
Limit_balance = st.number_input('Limit Balance', min_value=10000, max_value=999999999)
Pay_1 = st.selectbox('Repayment Status in September', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_2 = st.selectbox('Repayment Status in August', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_3 = st.selectbox('Repayment Status in July', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_4 = st.selectbox('Repayment Status in June', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_5 = st.selectbox('Repayment Status in May', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_6 = st.selectbox('Repayment Status in April', (-2,-1,0,1,2,3,4,5,6,7,8))
Pay_amt_1 = st.number_input('Bill Statement in September', min_value=-999999999, max_value=999999999)
Pay_amt_2 = st.number_input('Bill Statement in August', min_value=-999999999, max_value=999999999)
Pay_amt_3 = st.number_input('Bill Statement in July', min_value=-999999999, max_value=999999999)
Pay_amt_4 = st.number_input('Bill Statement in June', min_value=-999999999, max_value=999999999)
Pay_amt_5 = st.number_input('Bill Statement in May', min_value=-999999999, max_value=999999999)
Pay_amt_6 = st.number_input('Bill Statement in April', min_value=-999999999, max_value=999999999)
# Membuat tombol untuk melakukan prediksi
submitted = st.form_submit_button("Predict")
# dataframe
data = {'limit_balance': Limit_balance,
'pay_1': Pay_1,
'pay_2': Pay_2,
'pay_3': Pay_3,
'pay_4': Pay_4,
'pay_5': Pay_5,
'pay_6': Pay_6,
'pay_amt_1': Pay_amt_1,
'pay_amt_2': Pay_amt_2,
'pay_amt_3': Pay_amt_3,
'pay_amt_4': Pay_amt_4,
'pay_amt_5': Pay_amt_5,
'pay_amt_6': Pay_amt_6}
df = pd.DataFrame([data])
st.dataframe(df)
if submitted:
y_pred_inf = model.predict(df)
if y_pred_inf[0] == 0:
st.write('✅ Tidak Gagal Bayar')
else:
st.write('❌ Gagal Bayar')
if __name__== '__main__':
run() |