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Visual Analysis of Customer Satisfaction in Singapore's Hotel Industry: Uncovering Consumer Voices and Enhancing Service Quality
Data Analysis & Visualization (Web Scraper, Python, Plotly); Individual Project (2023)
Abstract
This study analyzes and visualizes customer satisfaction data for five-star hotels in Singapore, uncovering key trends and consumer preferences. By collecting multidimensional data from Booking.com, including hotel ratings, geographic locations, and service categories, the project employs Python and Plotly to develop innovative multi-level treemaps and geographic visualizations. These visualizations intuitively present hotel performance across service dimensions such as room quality, staff service, and facilities, while highlighting regional variations in customer satisfaction. Interactive features like hover-to-display and click-for-detailed-view enhance usability, enabling efficient data exploration. The proposed system offers hotel managers actionable insights to optimize strategic decisions, improve service quality, and strengthen customer satisfaction.
You can download the full report here.
And you may download my powerpoint presentation on the project here.
Demo Video
You can download my visualization system here.
Optimal Path Finding: Comparing Different Algorithms to Solve Mazes
Artificial Intelligence Research and Implementation (Python, Matplotlib); Group Project (2024)
Abstract
This project investigates the efficiency and effectiveness of various pathfinding algorithms in maze-solving applications. The algorithms compared include Depth-First Search (DFS), Breadth-First Search (BFS), A* Search, and Dijkstra's Algorithm. The study aims to provide a comprehensive understanding of the performance characteristics of each algorithm across different maze complexities and sizes. By generating mazes and analyzing the algorithms' execution times, path lengths, node visits and efficiency factor, the research identifies the optimal scenarios for each algorithm. The findings suggest that while BFS and Dijkstra's Algorithm excel in larger mazes due to their stability and efficiency, DFS is more suitable for smaller mazes. A* Algorithm, leveraging heuristics, offers a balanced performance across various conditions. These insights are valuable for developers and engineers in fields such as robotics, game development, and geographic information systems, where efficient pathfinding is crucial.
You can download the full report here.
And you may download my powerpoint presentation on the project here.
Travel Planner
Project Type
Mobile Application Development (Android Studio & Web)
Role
Individual Project (2023)
This prototype travel planning application, developed for Android and web platforms, integrates features like user registration, itinerary creation, Google Maps integration, and QR code generation. It highlights multi-platform compatibility with tools for booking, profile management, and interactive maps. While not a fully published app, it demonstrates the potential to streamline travel planning through a centralized and intuitive platform.
You can download my prototype here.
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