Update prediction.py

prediction.py

@@ -1,71 +1,77 @@
-import streamlit as st
-import pandas as pd
-import pickle
-
-# 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')
-
-    # 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()
+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()