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# Mengimpor library
import pandas as pd
from PIL import Image
import requests
from io import BytesIO
import streamlit as st
import pickle
# Menghilangkan warning
import warnings
warnings.filterwarnings("ignore")
# Menulis judul
st.markdown("<h1 style='text-align: center; '> Model Klasifikasi (Beli/Tidak) </h1>", unsafe_allow_html=True)
st.markdown('---'*10)
# Fungsi untuk prediksi
def final_prediction(values, model):
global prediction
prediction = model.predict(values)
return prediction
# Ini merupakan fungsi utama
def main():
# Nilai awal
usia = 25
gaji = 80000
with st.container():
col1, col2 = st.columns(2)
with col1:
usia = st.number_input('Usia', value=usia)
with col2:
gaji = st.number_input('Estimasi Gaji', value=gaji)
st.markdown('---'*10)
kelamin = st.selectbox('Jenis Kelamin', ('Laki', 'Perempuan'))
data = {
'Kelamin': kelamin,
'Usia':usia,
'EstimasiGaji': gaji
}
kolom = list(data.keys())
df_final = pd.DataFrame([data.values()],columns=kolom)
# load model
my_model = pickle.load(open('model_klasifikasi_terbaik.pkl', 'rb'))
# Predict
result = int(final_prediction(df_final, my_model))
hasil = []
if result==0:
hasil='Tidak Beli'
else:
hasil='Beli'
st.markdown('---'*10)
st.write('<center><b><h3>Predicted Beli/Tidak= ', hasil,'</b></h3>', unsafe_allow_html=True)
if __name__ == '__main__':
main()
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