<![CDATA[Healthcare services at Puskesmas Buntok often face challenges in managing patient queues, leading to long waiting times and decreased patient satisfaction. This study aims to design and implement an intelligent queue management system based on a website using FIFO (First In First Out) and Descending Priority Queue algorithms, as well as integrate wait time prediction using the Least Squares method in PHP Machine Learning. The software development methodology employed is the Waterfall model, encompassing requirement definition through flowchart creation, system and software design using UML (Use Case Diagram, Activity Diagram, and Class Diagram), implementation with PHP and MySQL, and system testing using black box testing and accuracy testing for the wait time prediction feature. The research results indicate that the developed intelligent queue system efficiently and effectively manages the order of patient services. The integration of wait time prediction provides accurate estimates, assists patients in planning their visits, and enhances the operational efficiency of the health center. System testing confirms that all functions operate as expected, making the website suitable for use as the official platform of Puskesmas Buntok. This implementation successfully improves the quality of healthcare services by reducing patient waiting times, increasing registration efficiency, and optimizing medical service processes through an innovative intelligent queue system]]>
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