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+FROM python:3.9-slim
+
+# Set environment variables
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PYTHONUNBUFFERED=1
+
+# Create a non-root user (Standard HF)
+RUN useradd -m -u 1000 user
+WORKDIR /home/user/app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install python dependencies globally as root
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application and set ownership
+COPY --chown=user:user . .
+
+# Expose port (HF requirement)
+EXPOSE 7860
+
+# Switch to user
+USER user
+
+# Run application with WebSocket & Custom Domain fixes
+CMD ["python", "-m", "streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0", "--browser.gatherUsageStats=false", "--server.enableCORS=false", "--server.enableXsrfProtection=false"]

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import io
+
+# Page Config
+st.set_page_config(page_title="All Anomaly Analysis", layout="wide")
+
+st.title('Aplikasi Analisa THC Pinjaman dan Simpanan')
+st.markdown("""
+## File yang dibutuhkan
+1. **Anomali Simpanan.xlsx**
+2. **Anomali Pinjaman.xlsx**
+3. **DbSimpanan.xlsx**
+    - Hapus bagian header terlebih dahulu
+    - Nama File harus DbSimpanan.xlsx dan sheet atau lembar nya IA_SimpananDB
+    """)
+
+def format_no(no):
+    try:
+        if pd.notna(no):
+            return f'{int(no):02d}.'
+        else:
+            return ''
+    except (ValueError, TypeError):
+        return str(no)
+
+def format_center(center):
+    try:
+        if pd.notna(center):
+            return f'{int(center):03d}'
+        else:
+            return ''
+    except (ValueError, TypeError):
+        return str(center)
+
+def format_kelompok(kelompok):
+    try:
+        if pd.notna(kelompok):
+            return f'{int(kelompok):02d}'
+        else:
+            return ''
+    except (ValueError, TypeError):
+        return str(kelompok)
+
+def load_data(uploaded_files):
+    dfs = {}
+    for file in uploaded_files:
+        try:
+            excel_file = pd.ExcelFile(file, engine='openpyxl')
+            
+            for sheet_name in excel_file.sheet_names:
+                df = pd.read_excel(excel_file, sheet_name=sheet_name)
+                key = f"{file.name}_{sheet_name}"
+                dfs[key] = df
+            
+            st.success(f"File {file.name} berhasil diunggah.")
+        except Exception as e:
+            st.error(f"Terjadi kesalahan saat memproses file {file.name}: {str(e)}")
+    return dfs
+
+def process_data(dfs):
+    try:
+        # Pinjaman
+        df_pu = dfs['Anomali Pinjaman.xlsx_Anomali PU'][['ID','CEK KRITERIA']].rename(columns={'CEK KRITERIA':'PU'})
+        df_pu['PU'] = df_pu['PU'].replace({True: 0, False: 1})
+
+        df_pmb = dfs['Anomali Pinjaman.xlsx_Anomali PMB'][['ID','CEK KRITERIA']].rename(columns={'CEK KRITERIA':'PMB'})
+        df_pmb['PMB'] = df_pmb['PMB'].replace({True: 0, False: 1})
+
+        df_psa = dfs['Anomali Pinjaman.xlsx_Anomali PSA'][['ID','CEK KRITERIA','Sukarela Sesuai','Wajib Sesuai','Pensiun Sesuai']]
+        df_psa[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']] = df_psa[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']].replace({True: 0, False: 1})
+        df_psa['PSA'] = df_psa[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']].sum(axis=1)
+        df_psa = df_psa[['ID','PSA']]
+
+        df_prr = dfs['Anomali Pinjaman.xlsx_Anomali PRR'][['ID','CEK KRITERIA','Sukarela Sesuai','Wajib Sesuai','Pensiun Sesuai']]
+        df_prr[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']] = df_prr[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']].replace({True: 0, False: 1})
+        df_prr['PRR'] = df_prr[['CEK KRITERIA', 'Sukarela Sesuai', 'Wajib Sesuai', 'Pensiun Sesuai']].sum(axis=1)
+        df_prr = df_prr[['ID','PRR']]
+
+        df_ptn = dfs['Anomali Pinjaman.xlsx_Anomali PTN'][['ID','SEMUA KRITERIA TERPENUHI']].rename(columns={'SEMUA KRITERIA TERPENUHI':'PTN'})
+        df_ptn['PTN'] = df_ptn['PTN'].replace({True: 0, False: 1})
+
+        df_arta = dfs['Anomali Pinjaman.xlsx_Anomali ARTA'][['ID','CEK KRITERIA']].rename(columns={'CEK KRITERIA':'ARTA'})
+        df_arta['ARTA'] = df_arta['ARTA'].replace({True: 0, False: 1})
+
+        df_dtp = dfs['Anomali Pinjaman.xlsx_Anomali DTP'][['ID','CEK KRITERIA']].rename(columns={'CEK KRITERIA':'DTP'})
+        df_dtp['DTP'] = df_dtp['DTP'].replace({True: 0, False: 1})
+
+        # Simpanan
+        df_sukarela = dfs['Anomali Simpanan.xlsx_Sukarela'][['ID','Transaksi > 0 & ≠ Modus Sukarela']].rename(columns={'Transaksi > 0 & ≠ Modus Sukarela':'SUKARELA'})
+        df_sihara = dfs['Anomali Simpanan.xlsx_Sihara'][['ID','TRANSAKSI TIDAK SESUAI']].rename(columns={'TRANSAKSI TIDAK SESUAI':'HARI RAYA'})
+        df_pensiun = dfs['Anomali Simpanan.xlsx_Pensiun'][['ID','Anomali']].rename(columns={'Anomali':'PENSIUN'})
+
+        # Merge all data
+        df_selected_all = dfs['DbSimpanan.xlsx_IA_SimpananDB'][['Client ID','Client Name','Center ID','Group ID','Meeting Day','Officer Name']].rename(columns={
+            'Client ID':'ID', 'Client Name': 'NAMA', 'Center ID': 'CENTER', 'Group ID': 'KELOMPOK', 'Meeting Day': 'HARI', 'Officer Name': 'STAF'
+        })
+
+        for df in [df_sukarela, df_pensiun, df_sihara, df_pu, df_pmb, df_psa, df_prr, df_ptn, df_arta, df_dtp]:
+            df_selected_all = df_selected_all.merge(df, on='ID', how='left')
+
+        df_selected_all = df_selected_all.fillna(0)
+
+        anomali_columns = ['SUKARELA', 'PENSIUN', 'HARI RAYA', 'PU', 'PMB', 'PSA', 'PRR', 'PTN', 'ARTA', 'DTP']
+        df_selected_all['TOTAL ANOMALI'] = df_selected_all[anomali_columns].sum(axis=1)
+
+        df_selected_all = df_selected_all[['ID', 'NAMA', 'CENTER', 'KELOMPOK', 'HARI', 'STAF'] + anomali_columns + ['TOTAL ANOMALI']]
+        df_selected_all = df_selected_all.drop_duplicates(subset=['ID', 'NAMA'])
+
+        # Pisahkan anomali simpanan dan pinjaman
+        anomali_simpanan = ['SUKARELA', 'PENSIUN', 'HARI RAYA']
+        anomali_pinjaman = ['PU', 'PMB', 'PSA', 'PRR', 'PTN', 'ARTA', 'DTP']
+
+        df_selected_all['Total Anomali Simpanan'] = df_selected_all[anomali_simpanan].sum(axis=1)
+        df_selected_all['Total Anomali Pinjaman'] = df_selected_all[anomali_pinjaman].sum(axis=1)
+
+        # Buat dictionary untuk memetakan hari bahasa Indonesia ke bahasa Inggris
+        hari_map = {
+            'SENIN': 'Monday',
+            'SELASA': 'Tuesday',
+            'RABU': 'Wednesday',
+            'KAMIS': 'Thursday',
+            'JUMAT': 'Friday',
+            'SABTU': 'Saturday',
+            'MINGGU': 'Sunday'
+        }
+
+        # Konversi kolom HARI ke bahasa Inggris
+        df_selected_all['HARI_EN'] = df_selected_all['HARI'].map(hari_map)
+
+        # Buat pivot table untuk setiap hari
+        pivot_dfs = []
+        for day in ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday', 'Sunday']:
+            sub_df = df_selected_all[df_selected_all['HARI_EN'] == day]
+            if not sub_df.empty:
+                pivot = sub_df.pivot_table(
+                    values=['Total Anomali Simpanan', 'Total Anomali Pinjaman'],
+                    index=['STAF', 'CENTER'],
+                    aggfunc='sum'
+                ).reset_index()
+        
+                pivot.columns = [f'{day}_{col}' if col not in ['STAF', 'CENTER'] else col for col in pivot.columns]
+                pivot_dfs.append(pivot)
+
+        # Gabungkan semua pivot table
+        if pivot_dfs:
+            result = pivot_dfs[0]
+            for df in pivot_dfs[1:]:
+                result = result.merge(df, on=['STAF', 'CENTER'], how='outer')
+
+            # Urutkan kolom
+            column_order = ['STAF', 'CENTER']
+            day_map_rev = {'Monday': 'SENIN', 'Tuesday': 'SELASA', 'Wednesday': 'RABU', 'Thursday': 'KAMIS', 'Friday': 'JUMAT', 'Saturday': 'SABTU', 'Sunday': 'MINGGU'}
+            
+            for day_en, day_id in day_map_rev.items():
+                s_col = f'{day_en}_Total Anomali Simpanan'
+                p_col = f'{day_en}_Total Anomali Pinjaman'
+                if s_col in result.columns: column_order.append(s_col)
+                if p_col in result.columns: column_order.append(p_col)
+
+            result = result.reindex(columns=column_order)
+
+            # Ganti nama kolom kembali ke bahasa Indonesia
+            new_columns = []
+            for col in result.columns:
+                temp_col = col
+                for day_en, day_id in day_map_rev.items():
+                    if day_en in temp_col:
+                        temp_col = temp_col.replace(day_en, day_id)
+                new_columns.append(temp_col.replace('_', ' '))
+            
+            result.columns = new_columns
+            result = result.fillna(0)
+        else:
+            result = pd.DataFrame(columns=['STAF', 'CENTER'])
+
+        return df_selected_all, result
+
+    except Exception as e:
+        st.error(f"Terjadi kesalahan saat memproses data: {str(e)}")
+        return None, None
+
+def main():
+    uploaded_files = st.file_uploader("Unggah file Excel", accept_multiple_files=True, type=["xlsx"])
+
+    if uploaded_files:
+        dfs = load_data(uploaded_files)
+        
+        required_files = [
+            'Anomali Pinjaman.xlsx_Anomali PU',
+            'Anomali Pinjaman.xlsx_Anomali PMB',
+            'Anomali Pinjaman.xlsx_Anomali DTP',
+            'Anomali Pinjaman.xlsx_Anomali PSA',
+            'Anomali Pinjaman.xlsx_Anomali ARTA',
+            'Anomali Pinjaman.xlsx_Anomali PRR',
+            'Anomali Pinjaman.xlsx_Anomali PTN',
+            'Anomali Simpanan.xlsx_Sihara',
+            'Anomali Simpanan.xlsx_Pensiun',
+            'Anomali Simpanan.xlsx_Sukarela',
+            'DbSimpanan.xlsx_IA_SimpananDB'
+        ]
+        
+        missing_files = [file for file in required_files if file not in dfs]
+        
+        if not missing_files:
+            with st.spinner("Sedang memproses data..."):
+                df_selected_all, result = process_data(dfs)
+            
+            if df_selected_all is not None and result is not None:
+                st.success("Proses selesai!")
+                
+                tabs = st.tabs(["Data Anomali", "Pivot Analysis"])
+                with tabs[0]:
+                    st.write("Data Anomali Gabungan:")
+                    st.dataframe(df_selected_all)
+                
+                with tabs[1]:
+                    st.write("Analisis Pivot per Hari:")
+                    st.dataframe(result)
+                
+                st.divider()
+                # Downloads
+                col1, col2 = st.columns(2)
+                with col1:
+                    buffer1 = io.BytesIO()
+                    with pd.ExcelWriter(buffer1, engine='xlsxwriter') as writer:
+                        df_selected_all.to_excel(writer, index=False, sheet_name='All Anomaly')
+                    st.download_button("Unduh Data Anomali.xlsx", buffer1.getvalue(), "Data_Anomali.xlsx")
+                
+                with col2:
+                    buffer2 = io.BytesIO()
+                    with pd.ExcelWriter(buffer2, engine='xlsxwriter') as writer:
+                        result.to_excel(writer, index=False, sheet_name='Pivot')
+                    st.download_button("Unduh Data Anomali Pivot.xlsx", buffer2.getvalue(), "Data_Anomali_Pivot.xlsx")
+        else:
+            st.warning(f"File/Sheet berikut belum lengkap: {', '.join(missing_files)}")
+
+if __name__ == "__main__":
+    main()

docker-compose.yml

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+services:
+  all-anomaly:
+    build: .
+    container_name: streamlit-all-anomaly
+    ports:
+      - "7863:7860"
+    restart: always
+    deploy:
+      resources:
+        limits:
+          memory: 2G
+    environment:
+      - STREAMLIT_SERVER_MAX_UPLOAD_SIZE=500

requirements.txt

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+streamlit
+pandas>=2.1.0
+numpy
+matplotlib
+openpyxl
+xlsxwriter
+pyarrow>=12.0.0