import streamlit as st def introduction(): # --- Sidebar --- st.sidebar.image("src/Amazon.png", use_container_width=True) st.sidebar.title("SalesBoost") st.sidebar.markdown(""" **Team Members** - 👩‍đŸ”Ŧ Avisa Rahma Benedicta (Data Scientist) - 👨‍đŸ’ģ Muhammad Farhan Hendriyanto (Data Engineer) - 👩‍đŸ”Ŧ Neila Ismahunnisa (Data Analyst) - 👩‍đŸ”Ŧ Sesilia Virdha Kezia (Data Scientist) """) st.sidebar.markdown(""" **Batch HCK-027** """) # --- Main Content --- st.title("🚀 SalesBoost Dashboard") st.markdown(""" SalesBoost is a project aimed at increasing sales by addressing a declining trend through accurate forecasting. It combines **customer behavior clustering** to uncover actionable segments for more effective promotions. This app delivers two key features: - 📈 **Sales Forecast Deployment** - đŸ‘Ĩ **Interactive Customer Dashboard** """) st.write("---") # --- Team --- st.title("Let's Meet Our Team") st.image("src/Team.jpg", use_container_width=True) st.write("---") # --- Sales Forecast Section --- st.header("📈 Predict Sales for the Next N Days") st.markdown("Slide the slider day and input quantity variables to generate sales forecasts.") st.write("---") # --- Customer Segmentation Section --- st.header("đŸ‘Ĩ Interactive Customer Clustering Dashboard") st.markdown("Explore customer behavior and segment patterns through clustering.") st.image("src/SalesBoost Overview Dashboard.png", caption="SalesBosst Overview Dashboard", use_container_width=True) st.write("---") st.image("src/SalesBoost Clustering.png", caption="SalesBosst After Clustering Dashboard", use_container_width=True) # Tombol untuk membuka Tableau tableau_url = "https://public.tableau.com/app/profile/muhammad.farhan.hendriyanto/viz/finalproject_17503214545810/DashboardSalesBoostAfterClustering?publish=yes" st.markdown(f"[🔗 Click here to open the dashboard in a new tab]({tableau_url})") st.info("Note: Due to Tableau Public's restrictions, this dashboard cannot be displayed directly in Streamlit.") st.write("---") # --- About Section --- st.header("â„šī¸ About SalesBoost") st.markdown(""" **Objective:** - Reverse the declining sales trend using intelligent forecasting and segmentation. **Methodology:** - Time Series Forecasting (SARIMAX) - Customer Clustering (K-Prototypes) - Dashboarding using Streamlit & Tableau **Deliverables:** - Forecast Deployment Page - Customer Segmentation Dashboard **Our Social Media:** - Instagram: - @farhend_27 - @neilaism - @sesiliakezia - @avisarahmab_ - @Rachman - Linkedin: - https://www.linkedin.com/in/muhammad-farhan-hendriyanto-48a0a320b/ - https://www.linkedin.com/in/neila-ismahunnisa/ - https://www.linkedin.com/in/sesilia-virdha-kezia-5922a736b/ - https://www.linkedin.com/in/avisa-rahma-benedicta-7b354a200/ - https://www.linkedin.com/in/rachman/ --- """) st.markdown("---") st.markdown("### 🙏 Ikan hiu makan tomat \ \ Thank you for exploring with us! 🙏") if __name__ == "__main__": introduction()