<![CDATA[The rapid advancement of smartphone technology has significantly influenced various aspects of student life, particularly in supporting academic and non-academic activities. Differences in user needs often cause students to experience difficulties in selecting smartphones that align with their usage preferences and financial capabilities. Therefore, a data grouping process is required to classify smartphones based on specific characteristics and user requirements. This study aims to classify smartphones according to student needs using the K-Means clustering method. The research employed a literature study approach by collecting data and references from scientific journals, articles, and various related sources discussing smartphone specifications and clustering techniques. Several variables used in this study include RAM capacity, internal storage, battery capacity, camera quality, chipset performance, and smartphone price. The K-Means algorithm was applied to group smartphones into several clusters based on similarities in specifications and usage characteristics. The results indicate that smartphones can be categorized into multiple groups, such as devices for academic purposes, gaming and multimedia needs, as well as content creation and photography activities. Keywords: K-Means, Clustering, Smartphone, Students, Data Mining]]>
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