Segmentasi Performa Kamar Hotel dengan Algoritma K-Means dan Strategi Pemasaran Menggunakan Dashboard Power BI - I Made Putra Sutresna Gita; Kartarina; Made Yadi Dharma; Ismarmiaty; Helna Wardhana (P3M STMIK LIKMI, 2026)
The tourism industry, particularly the hospitality sector in Indonesia, faces challenges in effectively managing room performance to support data-driven marketing strategies. Lomboks Hotel faces limitations in analyzing room performance because data processing is still done manually, making it less than optimal in supporting strategic decision-making. This study aims to apply the K-Means Clustering method to group room performance based on the number of guests, occupancy rate, room revenue, and occupancy level, as well as to design an interactive dashboard as a medium for visualizing the clustering results. The research methods include processing historical room data, the clustering process using K-Means Clustering, and presenting the results in the form of a visual dashboard. The results show the formation of three room performance clusters with distinct characteristics. The novelty of this study lies in the integration of data mining techniques and a visual decision support system for real-time monitoring of room performance. The conclusion indicates that this approach enhances the effectiveness of analysis and supports the formulation of more adaptive hotel marketing strategies