design layout fix
This commit is contained in:
Jesselyn Mu
33
App.py
33
App.py
@ -10,17 +10,13 @@ from pages.exploration import show_exploration
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from pages.karyawan_komen import show_karyawan_komen
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from pages.pimpinan_exploration import show_pimpinan_exploration
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# Set konfigurasi halaman sebagai perintah pertama
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st.set_page_config(page_title="Aplikasi Prediksi Retensi Karyawan", layout="wide", initial_sidebar_state="collapsed")
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st.set_page_config(page_title="TALENTRA", layout="wide", initial_sidebar_state="collapsed")
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# Tambahkan direktori 'App' ke sys.path
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sys.path.append(os.path.dirname(os.path.abspath(__file__)))
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# Import halaman dari folder pages
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import pages as pg
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# Import halaman dari root directory
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from login import show_login # Impor dari file login.py di root directory
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from login import show_login
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parent_dir = os.path.dirname(os.path.abspath(__file__))
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logo_path = os.path.join(parent_dir, "asset/logo.png")
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@ -51,7 +47,6 @@ st.markdown(
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unsafe_allow_html=True,
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)
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# CSS untuk mengubah warna latar belakang
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background_style = """
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<style>
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.stApp {
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@ -84,7 +79,6 @@ if "page" not in st.session_state:
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else:
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st.session_state.page = "Home"
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# Tambahkan validasi login
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if 'logged_in' in st.session_state and st.session_state['logged_in']:
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role = st.session_state.get('role', '').lower()
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role_pages = {
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@ -112,8 +106,7 @@ def get_image_as_base64(image_path):
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return base64.b64encode(img_file.read()).decode("utf-8")
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def navbar_with_sidebar_control(pages, options, logo_path):
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# Kontrol sidebar visibility
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if not options.get("show_sidebar", True): # Jika "show_sidebar" = False
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if not options.get("show_sidebar", True):
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st.markdown(
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"""
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<style>
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@ -125,7 +118,6 @@ def navbar_with_sidebar_control(pages, options, logo_path):
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unsafe_allow_html=True,
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)
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# Render navbar
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navbar_home()
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def navbar_home():
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@ -188,7 +180,7 @@ def navbar_home():
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</div>
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<div class="nav-links">
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<!-- Ganti teks "Home" dengan teks statis -->
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<span class="welcome-text">Selamat Datang di Aplikasi Prediksi Retensi Karyawan</span>
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<span class="welcome-text">Selamat Datang di TALENTRA</span>
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</div>
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<a class="login-button" href="?page=Login">Login</a>
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</div>
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@ -196,13 +188,11 @@ def navbar_home():
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unsafe_allow_html=True,
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)
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# Atur Navbar dengan kontrol sidebar
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options = {
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"show_menu": False,
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"show_sidebar": False, # Ubah ke True jika ingin menampilkan sidebar
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"show_sidebar": False,
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}
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# Atur Navbar dengan kontrol sidebar hanya untuk Home
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if st.session_state.page == "Home":
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navbar_with_sidebar_control(
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pages=["Home", "Login"],
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@ -210,24 +200,21 @@ if st.session_state.page == "Home":
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logo_path=logo_path,
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)
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# Deklarasi fungsi halaman
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functions = {
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"Home": pg.show_home,
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"Login": show_login, # Panggil fungsi show_login dari root directory
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"admin": show_prediction, # Pastikan fungsi ini diimpor dan didefinisikan
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"karyawan_form": show_karyawan_form, # Pastikan fungsi ini diimpor dan didefinisikan
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"Login": show_login,
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"admin": show_prediction,
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"karyawan_form": show_karyawan_form,
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"pimpinan_form": show_pimpinan_form,
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"exploration": show_exploration,
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"Prediksi": show_prediction, # Tambahkan ini
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"report": show_report, # Tambahkan ini
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"Prediksi": show_prediction,
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"report": show_report,
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"karyawan_komen": show_karyawan_komen,
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"pimpinan_exploration": show_pimpinan_exploration
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}
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query_params = st.query_params
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# Validasi query parameter
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if "page" not in st.session_state:
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query_params = st.query_params
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print("Query parameters (raw):", repr(query_params))
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14182
X_train.csv
14182
X_train.csv
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Before Width: | Height: | Size: 36 KiB After Width: | Height: | Size: 31 KiB |
2
login.py
2
login.py
@ -135,7 +135,7 @@ def show_login():
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color: white;
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font-family: 'Poppins', sans-serif;
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font-size: 16px;
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font-weight: 600;
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font-weight: 1000;
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border: none;
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border-radius: 5px;
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padding: 10px;
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9241
notebook/preprocessed_data_train_1.csv
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9241
notebook/preprocessed_data_train_1.csv
Normal file
File diff suppressed because it is too large
Load Diff
@ -6,194 +6,29 @@
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>employee_id</th>\n",
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" <th>domisili</th>\n",
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" <th>jenis_kelamin</th>\n",
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" <th>date_of_birth</th>\n",
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" <th>join_date</th>\n",
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" <th>resign_date</th>\n",
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" <th>marriage_stat</th>\n",
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" <th>dependant</th>\n",
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" <th>education</th>\n",
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" <th>absent_90D</th>\n",
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" <th>avg_time_work</th>\n",
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" <th>departemen</th>\n",
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" <th>position</th>\n",
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" <th>income</th>\n",
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" <th>total_komp</th>\n",
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" <th>job_satisfaction</th>\n",
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" <th>performance_rating</th>\n",
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" <th>churn_status</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>EM0001</td>\n",
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" <td>Kabupaten Bogor</td>\n",
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" <td>Laki-laki</td>\n",
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" <td>1970-09-10</td>\n",
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" <td>2024-01-04</td>\n",
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" <td>NaN</td>\n",
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" <td>Married</td>\n",
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" <td>2</td>\n",
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" <td>S1</td>\n",
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" <td>1.0</td>\n",
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" <td>9.34</td>\n",
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" <td>Engineering & IT</td>\n",
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" <td>Junior</td>\n",
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" <td>5198046</td>\n",
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" <td>NaN</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>EM0002</td>\n",
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" <td>Kota Jakarta Selatan</td>\n",
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" <td>Laki-laki</td>\n",
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" <td>1980-12-09</td>\n",
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" <td>2021-01-05</td>\n",
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" <td>2023-04-22</td>\n",
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" <td>Married</td>\n",
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" <td>3</td>\n",
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" <td>SLTA</td>\n",
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" <td>11.0</td>\n",
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" <td>9.86</td>\n",
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" <td>Service & Support</td>\n",
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" <td>Staff</td>\n",
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" <td>1281761</td>\n",
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" <td>NaN</td>\n",
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" <td>1</td>\n",
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" <td>2</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>EM0003</td>\n",
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" <td>Tangerang</td>\n",
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" <td>Laki-laki</td>\n",
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" <td>1987-04-25</td>\n",
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" <td>2022-01-17</td>\n",
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" <td>2024-01-31</td>\n",
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" <td>Single</td>\n",
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" <td>0</td>\n",
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" <td>D2</td>\n",
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" <td>3.0</td>\n",
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" <td>9.66</td>\n",
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" <td>Creative & Design</td>\n",
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" <td>Staff</td>\n",
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" <td>4902208</td>\n",
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" <td>NaN</td>\n",
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" <td>1</td>\n",
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" <td>3</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>EM0004</td>\n",
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" <td>Kepulauan Seribu</td>\n",
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" <td>Laki-laki</td>\n",
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" <td>1975-12-24</td>\n",
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" <td>2022-01-26</td>\n",
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" <td>NaN</td>\n",
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" <td>Married</td>\n",
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" <td>1</td>\n",
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" <td>S1</td>\n",
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" <td>1.0</td>\n",
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" <td>9.54</td>\n",
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" <td>Marketing</td>\n",
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" <td>Junior</td>\n",
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" <td>6410492</td>\n",
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" <td>NaN</td>\n",
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" <td>2</td>\n",
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" <td>1</td>\n",
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" <td>0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>EM0005</td>\n",
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" <td>Kota Jakarta Utara</td>\n",
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" <td>Laki-laki</td>\n",
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" <td>1987-06-15</td>\n",
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" <td>2022-01-31</td>\n",
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" <td>2023-02-21</td>\n",
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" <td>Single</td>\n",
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" <td>0</td>\n",
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" <td>SLTA</td>\n",
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" <td>1.0</td>\n",
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" <td>9.14</td>\n",
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" <td>Operations</td>\n",
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" <td>Staff</td>\n",
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" <td>1208627</td>\n",
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" <td>NaN</td>\n",
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" <td>2</td>\n",
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" <td>2</td>\n",
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" <td>1</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" employee_id domisili jenis_kelamin date_of_birth join_date \\\n",
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"0 EM0001 Kabupaten Bogor Laki-laki 1970-09-10 2024-01-04 \n",
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"1 EM0002 Kota Jakarta Selatan Laki-laki 1980-12-09 2021-01-05 \n",
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"2 EM0003 Tangerang Laki-laki 1987-04-25 2022-01-17 \n",
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"3 EM0004 Kepulauan Seribu Laki-laki 1975-12-24 2022-01-26 \n",
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"4 EM0005 Kota Jakarta Utara Laki-laki 1987-06-15 2022-01-31 \n",
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"\n",
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" resign_date marriage_stat dependant education absent_90D avg_time_work \\\n",
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"0 NaN Married 2 S1 1.0 9.34 \n",
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"1 2023-04-22 Married 3 SLTA 11.0 9.86 \n",
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"2 2024-01-31 Single 0 D2 3.0 9.66 \n",
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"3 NaN Married 1 S1 1.0 9.54 \n",
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"4 2023-02-21 Single 0 SLTA 1.0 9.14 \n",
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"\n",
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" departemen position income total_komp job_satisfaction \\\n",
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"0 Engineering & IT Junior 5198046 NaN 2 \n",
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"1 Service & Support Staff 1281761 NaN 1 \n",
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"2 Creative & Design Staff 4902208 NaN 1 \n",
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"3 Marketing Junior 6410492 NaN 2 \n",
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"4 Operations Staff 1208627 NaN 2 \n",
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"\n",
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" performance_rating churn_status \n",
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"0 2 0 \n",
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"1 2 1 \n",
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"2 3 1 \n",
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"3 1 0 \n",
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"4 2 1 "
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\lib\\site-packages\\numpy\\__init__.py:148: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see http://github.com/IntelPython/mkl-service\n",
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" from . import _distributor_init\n"
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]
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},
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{
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"ename": "ImportError",
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"evalue": "Unable to import required dependencies:\nnumpy: \n\nIMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!\n\nImporting the numpy C-extensions failed. This error can happen for\nmany reasons, often due to issues with your setup or how NumPy was\ninstalled.\n\nWe have compiled some common reasons and troubleshooting tips at:\n\n https://numpy.org/devdocs/user/troubleshooting-importerror.html\n\nPlease note and check the following:\n\n * The Python version is: Python3.10 from \"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\python.exe\"\n * The NumPy version is: \"1.21.5\"\n\nand make sure that they are the versions you expect.\nPlease carefully study the documentation linked above for further help.\n\nOriginal error was: No module named 'numpy.core._multiarray_umath'\n",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[0;32m 2\u001b[0m data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD:\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mTugas Akhir\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mCodingan\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mDevelopment\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mApp\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124motebook\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mpreprocessed_data_train_1.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 3\u001b[0m data\u001b[38;5;241m.\u001b[39mhead()\n",
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"File \u001b[1;32mc:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\lib\\site-packages\\pandas\\__init__.py:16\u001b[0m\n\u001b[0;32m 13\u001b[0m missing_dependencies\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdependency\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00me\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m missing_dependencies:\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[0;32m 17\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnable to import required dependencies:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(missing_dependencies)\n\u001b[0;32m 18\u001b[0m )\n\u001b[0;32m 19\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m hard_dependencies, dependency, missing_dependencies\n\u001b[0;32m 21\u001b[0m \u001b[38;5;66;03m# numpy compat\u001b[39;00m\n",
|
||||
"\u001b[1;31mImportError\u001b[0m: Unable to import required dependencies:\nnumpy: \n\nIMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!\n\nImporting the numpy C-extensions failed. This error can happen for\nmany reasons, often due to issues with your setup or how NumPy was\ninstalled.\n\nWe have compiled some common reasons and troubleshooting tips at:\n\n https://numpy.org/devdocs/user/troubleshooting-importerror.html\n\nPlease note and check the following:\n\n * The Python version is: Python3.10 from \"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\python.exe\"\n * The NumPy version is: \"1.21.5\"\n\nand make sure that they are the versions you expect.\nPlease carefully study the documentation linked above for further help.\n\nOriginal error was: No module named 'numpy.core._multiarray_umath'\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import pandas as pd\n",
|
||||
"data = pd.read_csv('D:\\Tugas Akhir\\Codingan\\Development\\Data\\data_train.csv')\n",
|
||||
"data = pd.read_csv('D:\\Tugas Akhir\\Codingan\\Development\\App\\notebook\\preprocessed_data_train_1.csv')\n",
|
||||
"data.head()"
|
||||
]
|
||||
},
|
||||
@ -5375,7 +5210,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.18"
|
||||
"version": "3.10.16"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -23,224 +23,24 @@
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>employee_id</th>\n",
|
||||
" <th>domisili</th>\n",
|
||||
" <th>jenis_kelamin</th>\n",
|
||||
" <th>date_of_birth</th>\n",
|
||||
" <th>join_date</th>\n",
|
||||
" <th>resign_date</th>\n",
|
||||
" <th>marriage_stat</th>\n",
|
||||
" <th>dependant</th>\n",
|
||||
" <th>education</th>\n",
|
||||
" <th>absent_90D</th>\n",
|
||||
" <th>...</th>\n",
|
||||
" <th>active_work_category</th>\n",
|
||||
" <th>work_stability_score</th>\n",
|
||||
" <th>married_dependent_ratio</th>\n",
|
||||
" <th>position_score</th>\n",
|
||||
" <th>job_income_position_score</th>\n",
|
||||
" <th>education_score</th>\n",
|
||||
" <th>education_income_ratio</th>\n",
|
||||
" <th>weighted_satisfaction_performance</th>\n",
|
||||
" <th>resign_risk_indicator</th>\n",
|
||||
" <th>adjusted_work_time</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>EM0001</td>\n",
|
||||
" <td>Kabupaten Bogor</td>\n",
|
||||
" <td>Laki-laki</td>\n",
|
||||
" <td>1970-09-10</td>\n",
|
||||
" <td>2024-01-04</td>\n",
|
||||
" <td>2024-10-31</td>\n",
|
||||
" <td>Married</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>S1</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>Short-term</td>\n",
|
||||
" <td>5.00</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>2599023.0</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>1.039609e+06</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>Medium</td>\n",
|
||||
" <td>9.329634</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1</th>\n",
|
||||
" <td>EM0002</td>\n",
|
||||
" <td>Kota Jakarta Selatan</td>\n",
|
||||
" <td>Laki-laki</td>\n",
|
||||
" <td>1980-12-09</td>\n",
|
||||
" <td>2021-01-05</td>\n",
|
||||
" <td>2023-04-22</td>\n",
|
||||
" <td>Married</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>SLTA</td>\n",
|
||||
" <td>11.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>Mid-term</td>\n",
|
||||
" <td>2.25</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1281761.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1.281761e+06</td>\n",
|
||||
" <td>1.4</td>\n",
|
||||
" <td>Medium</td>\n",
|
||||
" <td>9.815385</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2</th>\n",
|
||||
" <td>EM0003</td>\n",
|
||||
" <td>Tangerang</td>\n",
|
||||
" <td>Laki-laki</td>\n",
|
||||
" <td>1987-04-25</td>\n",
|
||||
" <td>2022-01-17</td>\n",
|
||||
" <td>2024-01-31</td>\n",
|
||||
" <td>Single</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>D2</td>\n",
|
||||
" <td>3.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>Mid-term</td>\n",
|
||||
" <td>6.00</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>4902208.0</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>1.634069e+06</td>\n",
|
||||
" <td>1.8</td>\n",
|
||||
" <td>Medium</td>\n",
|
||||
" <td>9.646590</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>EM0004</td>\n",
|
||||
" <td>Kepulauan Seribu</td>\n",
|
||||
" <td>Laki-laki</td>\n",
|
||||
" <td>1975-12-24</td>\n",
|
||||
" <td>2022-01-26</td>\n",
|
||||
" <td>2024-10-31</td>\n",
|
||||
" <td>Married</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>S1</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>Mid-term</td>\n",
|
||||
" <td>16.50</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>3205246.0</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>1.282098e+06</td>\n",
|
||||
" <td>1.6</td>\n",
|
||||
" <td>Medium</td>\n",
|
||||
" <td>9.536789</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4</th>\n",
|
||||
" <td>EM0005</td>\n",
|
||||
" <td>Kota Jakarta Utara</td>\n",
|
||||
" <td>Laki-laki</td>\n",
|
||||
" <td>1987-06-15</td>\n",
|
||||
" <td>2022-01-31</td>\n",
|
||||
" <td>2023-02-21</td>\n",
|
||||
" <td>Single</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>SLTA</td>\n",
|
||||
" <td>1.0</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>Mid-term</td>\n",
|
||||
" <td>6.00</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1208627.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>1.208627e+06</td>\n",
|
||||
" <td>2.0</td>\n",
|
||||
" <td>Medium</td>\n",
|
||||
" <td>9.131545</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>5 rows × 37 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" employee_id domisili jenis_kelamin date_of_birth join_date \\\n",
|
||||
"0 EM0001 Kabupaten Bogor Laki-laki 1970-09-10 2024-01-04 \n",
|
||||
"1 EM0002 Kota Jakarta Selatan Laki-laki 1980-12-09 2021-01-05 \n",
|
||||
"2 EM0003 Tangerang Laki-laki 1987-04-25 2022-01-17 \n",
|
||||
"3 EM0004 Kepulauan Seribu Laki-laki 1975-12-24 2022-01-26 \n",
|
||||
"4 EM0005 Kota Jakarta Utara Laki-laki 1987-06-15 2022-01-31 \n",
|
||||
"\n",
|
||||
" resign_date marriage_stat dependant education absent_90D ... \\\n",
|
||||
"0 2024-10-31 Married 2 S1 1.0 ... \n",
|
||||
"1 2023-04-22 Married 3 SLTA 11.0 ... \n",
|
||||
"2 2024-01-31 Single 0 D2 3.0 ... \n",
|
||||
"3 2024-10-31 Married 1 S1 1.0 ... \n",
|
||||
"4 2023-02-21 Single 0 SLTA 1.0 ... \n",
|
||||
"\n",
|
||||
" active_work_category work_stability_score married_dependent_ratio \\\n",
|
||||
"0 Short-term 5.00 3 \n",
|
||||
"1 Mid-term 2.25 4 \n",
|
||||
"2 Mid-term 6.00 1 \n",
|
||||
"3 Mid-term 16.50 2 \n",
|
||||
"4 Mid-term 6.00 1 \n",
|
||||
"\n",
|
||||
" position_score job_income_position_score education_score \\\n",
|
||||
"0 2 2599023.0 5 \n",
|
||||
"1 1 1281761.0 1 \n",
|
||||
"2 1 4902208.0 3 \n",
|
||||
"3 2 3205246.0 5 \n",
|
||||
"4 1 1208627.0 1 \n",
|
||||
"\n",
|
||||
" education_income_ratio weighted_satisfaction_performance \\\n",
|
||||
"0 1.039609e+06 2.0 \n",
|
||||
"1 1.281761e+06 1.4 \n",
|
||||
"2 1.634069e+06 1.8 \n",
|
||||
"3 1.282098e+06 1.6 \n",
|
||||
"4 1.208627e+06 2.0 \n",
|
||||
"\n",
|
||||
" resign_risk_indicator adjusted_work_time \n",
|
||||
"0 Medium 9.329634 \n",
|
||||
"1 Medium 9.815385 \n",
|
||||
"2 Medium 9.646590 \n",
|
||||
"3 Medium 9.536789 \n",
|
||||
"4 Medium 9.131545 \n",
|
||||
"\n",
|
||||
"[5 rows x 37 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\lib\\site-packages\\numpy\\__init__.py:148: UserWarning: mkl-service package failed to import, therefore Intel(R) MKL initialization ensuring its correct out-of-the box operation under condition when Gnu OpenMP had already been loaded by Python process is not assured. Please install mkl-service package, see http://github.com/IntelPython/mkl-service\n",
|
||||
" from . import _distributor_init\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"ename": "ImportError",
|
||||
"evalue": "Unable to import required dependencies:\nnumpy: \n\nIMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!\n\nImporting the numpy C-extensions failed. This error can happen for\nmany reasons, often due to issues with your setup or how NumPy was\ninstalled.\n\nWe have compiled some common reasons and troubleshooting tips at:\n\n https://numpy.org/devdocs/user/troubleshooting-importerror.html\n\nPlease note and check the following:\n\n * The Python version is: Python3.10 from \"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\python.exe\"\n * The NumPy version is: \"1.21.5\"\n\nand make sure that they are the versions you expect.\nPlease carefully study the documentation linked above for further help.\n\nOriginal error was: No module named 'numpy.core._multiarray_umath'\n",
|
||||
"output_type": "error",
|
||||
"traceback": [
|
||||
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
||||
"\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)",
|
||||
"Cell \u001b[1;32mIn[1], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[0;32m 3\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mD:\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mTugas Akhir\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mCodingan\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mDevelopment\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mData\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124mpreprocessed_data_train.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 4\u001b[0m df\u001b[38;5;241m.\u001b[39mhead()\n",
|
||||
"File \u001b[1;32mc:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\lib\\site-packages\\pandas\\__init__.py:16\u001b[0m\n\u001b[0;32m 13\u001b[0m missing_dependencies\u001b[38;5;241m.\u001b[39mappend(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdependency\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00me\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m missing_dependencies:\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[0;32m 17\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnable to import required dependencies:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(missing_dependencies)\n\u001b[0;32m 18\u001b[0m )\n\u001b[0;32m 19\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m hard_dependencies, dependency, missing_dependencies\n\u001b[0;32m 21\u001b[0m \u001b[38;5;66;03m# numpy compat\u001b[39;00m\n",
|
||||
"\u001b[1;31mImportError\u001b[0m: Unable to import required dependencies:\nnumpy: \n\nIMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!\n\nImporting the numpy C-extensions failed. This error can happen for\nmany reasons, often due to issues with your setup or how NumPy was\ninstalled.\n\nWe have compiled some common reasons and troubleshooting tips at:\n\n https://numpy.org/devdocs/user/troubleshooting-importerror.html\n\nPlease note and check the following:\n\n * The Python version is: Python3.10 from \"c:\\Users\\Jesselyn Mu\\anaconda3\\envs\\myenv\\python.exe\"\n * The NumPy version is: \"1.21.5\"\n\nand make sure that they are the versions you expect.\nPlease carefully study the documentation linked above for further help.\n\nOriginal error was: No module named 'numpy.core._multiarray_umath'\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
@ -2199,7 +1999,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.18"
|
||||
"version": "3.10.16"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -241,11 +241,13 @@ def show_home():
|
||||
<div class="text-content">
|
||||
<h2 class="section-title">Bagian Aplikasi</h2>
|
||||
<p style="text-align: justify;">
|
||||
Aplikasi ini dirancang untuk mendukung prediksi retensi karyawan dan pengelolaan data dengan fitur-fitur yang terstruktur berdasarkan peran pengguna.
|
||||
Halaman login menjadi pintu masuk utama untuk autentikasi, setelah itu pengguna diarahkan ke halaman sesuai perannya: admin, karyawan, atau pimpinan.
|
||||
Admin memiliki akses ke halaman prediksi untuk analisis data, dashboard untuk memantau statistik, dan halaman laporan untuk melihat detail data.
|
||||
Karyawan dapat mengisi form kepuasan kerja untuk memberikan umpan balik terkait pengalaman mereka.
|
||||
Sementara itu, pimpinan dapat menggunakan dashboard untuk melihat data strategis serta mengisi form penilaian kinerja guna mengevaluasi performa karyawan.
|
||||
Aplikasi ini dirancang untuk mendukung prediksi retensi karyawan dan pengelolaan data
|
||||
dengan fitur-fitur yang terstruktur berdasarkan peran pengguna.
|
||||
Dimulai dari Halaman Utama, pengguna diarahkan ke Halaman Login,
|
||||
yang kemudian membagi akses berdasarkan peran: Admin, Karyawan, dan Pimpinan.
|
||||
Admin memiliki akses ke Halaman Prediksi, Halaman Dashboard, dan Halaman Laporan untuk mengelola data dan analisis.
|
||||
Karyawan dapat mengisi Form Kepuasan Kerja dan Form Komplain untuk memberikan feedback dan keluhan.
|
||||
Pimpinan memiliki akses ke Form Penilaian untuk evaluasi serta Halaman Dashboard untuk melihat data yang relevan.
|
||||
Aplikasi ini dirancang untuk mempermudah pengelolaan dan pengambilan keputusan berbasis data.
|
||||
</p>
|
||||
</div>
|
||||
@ -254,7 +256,6 @@ def show_home():
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
|
||||
# Berita dan Informasi
|
||||
st.markdown(
|
||||
f"""
|
||||
<div class="news-section">
|
||||
@ -274,7 +275,6 @@ def show_home():
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
|
||||
# Footer
|
||||
st.markdown(
|
||||
"""
|
||||
<div class="footer">
|
||||
@ -285,13 +285,10 @@ def show_home():
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
|
||||
|
||||
def get_image_as_base64(image_path):
|
||||
import base64
|
||||
with open(image_path, "rb") as img_file:
|
||||
return base64.b64encode(img_file.read()).decode("utf-8")
|
||||
|
||||
|
||||
# Jalankan aplikasi
|
||||
if __name__ == "__main__":
|
||||
show_home()
|
||||
@ -462,41 +462,7 @@ def show_prediction():
|
||||
col1, col2 = st.columns([1.5, 2]) # **Kolom pertama untuk grafik, kolom kedua untuk penjelasan**
|
||||
|
||||
with col1:
|
||||
# st.image(buf, caption="SHAP Waterfall Plot", use_container_width=True)
|
||||
# Tambahkan CSS styling ke HTML
|
||||
st.markdown(
|
||||
"""
|
||||
<style>
|
||||
.shap-container {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
margin-top: 10px;
|
||||
}
|
||||
.shap-image {
|
||||
border-radius: 10px; /* Sudut membulat */
|
||||
box-shadow: 4px 4px 10px rgba(0, 0, 0, 0.2); /* Shadow */
|
||||
border: 2px solid #ddd; /* Stroke */
|
||||
padding: 5px; /* Ruang di dalam border */
|
||||
background: white; /* Biar keliatan efeknya */
|
||||
max-width: 100%; /* Biar responsif */
|
||||
}
|
||||
.shap-caption {
|
||||
text-align: center;
|
||||
font-size: 14px;
|
||||
font-family: 'Poppins', sans-serif;
|
||||
color: #555;
|
||||
margin-top: 5px;
|
||||
}
|
||||
</style>
|
||||
""",
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
|
||||
# Gunakan `st.image()` untuk menampilkan gambar SHAP dari `buf`
|
||||
st.markdown('<div class="shap-container">', unsafe_allow_html=True)
|
||||
st.image(buf, caption="SHAP Waterfall Plot", use_container_width=True)
|
||||
st.markdown('</div>', unsafe_allow_html=True)
|
||||
|
||||
with col2:
|
||||
top_factors = sorted(shap_dict.items(), key=lambda x: abs(x[1]), reverse=True)[:5]
|
||||
|
||||
Reference in New Issue
Block a user