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| # import library yang dibutuhkan | |
| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| import joblib | |
| # load best model | |
| with open('catb_randcv.pkl','rb') as file_1: | |
| catb_pipe = joblib.load(file_1) | |
| # Construct Data Infer | |
| # define semua fitur/kolom | |
| features = ['Gender','Customer Type','Age','Type of Travel','Class','Flight Distance',\ | |
| 'Inflight wifi service','Departure/Arrival time convenient','Ease of Online booking',\ | |
| 'Gate location','Food and drink','Online boarding','Seat comfort','Inflight entertainment',\ | |
| 'On-board service','Leg room service','Baggage handling','Checkin service','Inflight service',\ | |
| 'Cleanliness','Departure Delay in Minutes','Arrival Delay in Minutes'] | |
| def infer(data_infer): | |
| # predict result with pre-trained model | |
| pred = catb_pipe.predict(data_infer) | |
| return pred | |
| # header deployment | |
| st.header("Predicting Passenger Flight Satisfaction") | |
| # artificial data infer | |
| gender_options = ["Male", "Female"] | |
| gender = st.selectbox("Please input your gender: ", gender_options) | |
| customer_type_options = ['Loyal Customer', 'disloyal Customer'] | |
| customer_type = st.selectbox("Which type of customer are you? ", customer_type_options) | |
| type_of_travel_options = ['Personal Travel', 'Business travel'] | |
| type_of_travel = st.selectbox("Please input your type of travel: ", type_of_travel_options) | |
| class_options = ['Eco', 'Eco Plus', 'Business'] | |
| class_ = st.selectbox("Please input your flight class: ", class_options) | |
| age = st.slider("Please input your age: ",0,100) | |
| flight_distance = st.slider("Please input your flight distance (in Miles): ",0,5000) | |
| wifi_service = st.slider("Please input your wifi experience (0\:lowest 5\:highest) ",0,5) | |
| departure_arrival_conv = st.slider("Please input your departure or arrival time convenience experience (0\:lowest 5\:highest)",0,5) | |
| online_booking_exp = st.slider("Please input your online booking experience (0\:lowest 5\:highest)",0,5) | |
| gate_loc_exp = st.slider("Please input your gate location experience (0\:lowest 5\:highest)",0,5) | |
| food_drinks_exp = st.slider("Please input your food & drinks experience (0\:lowest 5\:highest)",0,5) | |
| online_boarding_exp = st.slider("Please input your online boarding experience (0\:lowest 5\:highest)",0,5) | |
| seat_comfort_exp = st.slider("Please input your seat comfort experience (0\:lowest 5\:highest)",0,5) | |
| inflight_entertainment_exp = st.slider("Please input your inflight entertainment experience (0\:lowest 5\:highest)",0,5) | |
| on_board_svc_exp = st.slider("Please input your on-board service experience (0\:lowest 5\:highest)",0,5) | |
| leg_room_svc_exp = st.slider("Please input your leg room service experience (0\:lowest 5\:highest)",0,5) | |
| baggage_handling_exp = st.slider("Please input your baggage handling experience (0\:lowest 5\:highest)",0,5) | |
| checkin_svc_exp = st.slider("Please input your check-in service experience (0\:lowest 5\:highest)",0,5) | |
| inflight_svc_exp = st.slider("Please input your inflight service experience (0\:lowest 5\:highest)",0,5) | |
| cleanliness = st.slider("How do you rate our cleanliness? (0\:lowest 5\:highest)\: ",0,5) | |
| depart_delay = st.slider("Did you experience delay in your departure? if so please specify (in minutes): ",0,1500) | |
| arriv_delay = st.slider("Did you experience delay in your arrival? if so please specify (in minutes): ",0,1500) | |
| if st.button("Submit"): | |
| D = { | |
| 'Gender':gender, | |
| 'Customer Type':customer_type, | |
| 'Age':age, | |
| 'Type of Travel':type_of_travel, | |
| 'Class':class_, | |
| 'Flight Distance':flight_distance, | |
| 'Inflight wifi service':wifi_service, | |
| 'Departure/Arrival time convenient':departure_arrival_conv, | |
| 'Ease of Online booking':online_booking_exp, | |
| 'Gate location':gate_loc_exp, | |
| 'Food and drink':food_drinks_exp, | |
| 'Online boarding':online_boarding_exp, | |
| 'Seat comfort':seat_comfort_exp, | |
| 'Inflight entertainment':inflight_entertainment_exp, | |
| 'On-board service':on_board_svc_exp, | |
| 'Leg room service':leg_room_svc_exp, | |
| 'Baggage handling':baggage_handling_exp, | |
| 'Checkin service':checkin_svc_exp, | |
| 'Inflight service':inflight_svc_exp, | |
| 'Cleanliness':cleanliness, | |
| 'Departure Delay in Minutes':depart_delay, | |
| 'Arrival Delay in Minutes':arriv_delay, | |
| } | |
| # construct data inference dalam dataframe | |
| data_infer = pd.DataFrame(data=D,columns=features,index=[0]) | |
| #panggil fungsi inference | |
| pred = infer(data_infer) | |
| st.header(f"Prediction Result: ") | |
| st.write("You are most likely " + pred[0] + " with your flight experience") | |