Choosing the optimal smartphone for streaming needs is a challenge for users amidst the rapid development of technology and the variety of choices on the market. The need for high performance in streaming, such as large battery capacity, adequate RAM, fast processor, high-quality screen, and stable network support, drives the need for an objective and measurable recommendation system. This study aims to develop a smartphone selection recommendation system using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method that focuses on streaming activity needs. The research process involves the stages of problem identification, collecting datasets from various trusted sources, preprocessing data to ensure completeness and consistency, and implementing the TOPSIS method through data normalization, weighting criteria, determining positive and negative ideal solutions, to calculating preference scores and alternative rankings. The dataset used includes 252 smartphones from popular brands in Indonesia such as Samsung, Oppo, Vivo, Apple, Realme, and Xiaomi, with specifications relevant to streaming. The results of the TOPSIS method implementation show that smartphones such as the iQOO Z9 Turbo Endurance, Redmi Turbo4, and Neo7 SE are ranked at the top with high preference scores, indicating the best combination of price, battery capacity, RAM, and network connectivity. The recommendation categories are arranged based on market segments, such as flagship, mid-range, budget-friendly , and based on each brand, to provide flexibility in selection. In general, Vivo, Xiaomi, and Realme dominate the best category, while Samsung and Oppo remain competitive in the middle class, and Apple maintains its stability in the premium ecosystem. The recommendation system is expected to help users make faster and more precise decisions according to technical needs and budget constraints in choosing a smartphone for high-quality streaming activities.
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