Developing an AI-driven Web Application for Predicting User Behavior and Recommending Resort Room Bookings with a Geographic Map-Based Resort Room Data Management System

Abstract

This research has two main objectives: 1) to analyze, design, and develop a web application that predicts user behavior to recommend resort room bookings using artificial intelligence, integrated with a geospatial room management system, and 2) to assess the effectiveness of the web application in predicting behavior and recommending resort room bookings, combined with a geospatial room management system. The data used in the experiment includes resort information, room details, room types, and room reservation data. The research tools include the development of a predictive behavior web application connected to a MySQL database, utilizing PHP, HTML, and Bootstrap 4. Data collection tools involve performance evaluation surveys. The project follows the Software Development Life Cycle (SDLC), and the web application’s performance is evaluated by five experts selected through purposive sampling. The results of the project development found that: 1) the web application for predicting user behavior and recommending resort room bookings with a geographic map-based resort room data management system allows customers to register, edit their personal information, make and cancel reservations, specify the current locations of the resorts, and use artificial intelligence technology to predict room booking behavior, which meets the set objectives; and 2) the performance evaluation results ̅=4.87, S.D.=0.23). by five experts are at the highest level (X