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import streamlit as st
import pandas as pd
import pickle
from PIL import Image
# Path to the model file
model_path = "model.pkl"
# Load the model
with open(model_path, 'rb') as f:
model = pickle.load(f)
def run():
st.title('Prediksi Pengunduran Diri Karyawan')
st.markdown('---')
image = Image.open('image_prediction.jpg')
st.image(image)
# Membuat Garis lurus
st.markdown('---')
# Formulir untuk pengisian data
with st.form('form_employee_attrition'):
# Kolom input sesuai dengan keterangan yang Anda berikan
business_travel = st.selectbox('Business Travel', ['Travel_Rarely', 'Travel_Frequently', 'Non-Travel'])
department = st.selectbox('Department', ['Sales', 'Research & Development', 'Human Resources'])
education_field = st.selectbox('Education Field', ['Life Sciences', 'Other', 'Medical', 'Marketing', 'Technical Degree', 'Human Resources'])
job_role = st.selectbox('Job Role', ['Healthcare Representative', 'Research Scientist', 'Sales Executive', 'Human Resources', 'Research Director', 'Laboratory Technician', 'Manufacturing Director', 'Sales Representative', 'Manager'])
marital_status = st.selectbox('Marital Status', ['Married', 'Single', 'Divorced'])
training_times_last_year = st.selectbox('Training Times Last Year', [0, 1, 2, 3, 4, 5, 6])
job_involvement = st.selectbox('Job Involvement', [1, 2, 3, 4], format_func=lambda x: {1: 'Low', 2: 'Medium', 3: 'High', 4: 'Very High'}[x])
environment_satisfaction = st.selectbox('Environment Satisfaction', [1, 2, 3, 4], format_func=lambda x: {1: 'Low', 2: 'Medium', 3: 'High', 4: 'Very High'}[x])
job_satisfaction = st.selectbox('Job Satisfaction', [1, 2, 3, 4], format_func=lambda x: {1: 'Low', 2: 'Medium', 3: 'High', 4: 'Very High'}[x])
work_life_balance = st.selectbox('Work Life Balance', [1, 2, 3, 4], format_func=lambda x: {1: 'Bad', 2: 'Good', 3: 'Better', 4: 'Best'}[x])
age = st.slider('Age', min_value=18, max_value=60)
percent_salary_hike = st.slider('Percent Salary Hike', min_value=11, max_value=25)
total_working_years = st.slider('Total Working Years', min_value=0, max_value=40)
years_at_company = st.slider('Years At Company', min_value=0, max_value=40)
years_since_last_promotion = st.slider('Years Since Last Promotion', min_value=0, max_value=15)
years_with_curr_manager = st.slider('Years With Current Manager', min_value=0, max_value=17)
# Tombol untuk melakukan prediksi
submitted = st.form_submit_button('Prediksi')
# Menyusun data input menjadi DataFrame
data = {
'BusinessTravel': business_travel,
'Department': department,
'EducationField': education_field,
'JobRole': job_role,
'MaritalStatus': marital_status,
'TrainingTimesLastYear': training_times_last_year,
'JobInvolvement': job_involvement,
'EnvironmentSatisfaction': environment_satisfaction,
'JobSatisfaction': job_satisfaction,
'WorkLifeBalance': work_life_balance,
'Age': age,
'PercentSalaryHike': percent_salary_hike,
'TotalWorkingYears': total_working_years,
'YearsAtCompany': years_at_company,
'YearsSinceLastPromotion': years_since_last_promotion,
'YearsWithCurrManager': years_with_curr_manager
}
features = pd.DataFrame(data, index=[0])
# Menampilkan fitur input pengguna
st.write("## Fitur Input Pengguna")
st.write(features)
# Melakukan prediksi jika tombol prediksi ditekan
if submitted:
prediction = model.predict(features)
st.subheader('Hasil Prediksi')
st.write('Pengunduran Diri Karyawan:', 'Ya' if prediction[0] == 1 else 'Tidak')
if __name__ == '__main__':
run()
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