<![CDATA[Research This research applies the K-Means Clustering method to identify groups of hotel guests based on their room preferences, duration of stay and level of satisfaction. The results of this research have great potential to help hotel management improve service quality and marketing strategies. The main focus of the research is on guest satisfaction and resource optimization. Using K-Means Clustering data analysis, this research aims to uncover common patterns among hotel guests, enabling management to allocate resources more efficiently. By understanding guest preferences regarding rooms and length of stay, management can better customize their hotel services and facilities. Apart from that, this research also aims to increase guest satisfaction by identifying factors that influence satisfaction levels. With a deeper understanding of guest needs and preferences, management can take appropriate steps to improve the guest experience. The results of this research can also have significant marketing implications. By understanding different guest profiles, hotels can design more effective marketing strategies and target specific promotions to specific groups of guests based on their characteristics. Overall, this research has the potential to help hotels improve guest satisfaction and operational efficiency through better understanding guest preferences and grouping them based on certain factors.]]>
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