<![CDATA[The increasing use of smartphones necessitates rational decision-making about device upgrades. Many users upgrade without considering the actual device condition and usage requirements. This study aims to develop an artificial intelligence-based recommendation system to objectively determine smartphone upgrade decisions. The method used is the C4.5 algorithm for classification based on device specifications and usage patterns. The dataset consists of 100 records, including 80 for training and 20 for testing. The results show that the system successfully generates a representative decision tree model. Performance evaluation using a confusion matrix yields an accuracy of 95.00 percent, categorized as excellent. The system is also integrated with AI Gemini to generate narrative explanations from classification results, improving interpretability. The contribution lies in integrating classification algorithms with generative models to produce accurate and informative recommendations. This system provides a practical solution for users to efficiently determine smartphone upgrade needs.]]>
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