Purpose: Online motorcycle taxi (ojek online) drivers in Indonesia require smartphones that support intensive all-day outdoor use, including strong battery life, performance, screen visibility, and network stability. This study aims to develop a web-based Decision Support System (DSS) using the SMART (Simple Multi Attribute Rating Technique) method to recommend the most suitable smartphone based on occupation-specific criteria.
Methodology: A design and development research approach was used. Ten criteria were identified through observation and interviews, including price, battery capacity, processor, storage, RAM, screen brightness, network technology, display size, and camera quality. Four Oppo smartphones (A12, A16K, A52, and F11) were evaluated. Criteria weights were assigned based on driver priorities, then normalized. Utility values were calculated using the SMART formula, and final scores were obtained from weighted utility aggregation.
Results: The SMART analysis ranked Oppo F11 first (Nta = 70.5), followed by Oppo A52 (59.2), Oppo A12 (45.8), and Oppo A16K (37.9). The F11 achieved the highest score due to its balanced affordability, strong chipset performance, large storage, and adequate RAM capacity.
Conclusions: The SMART-based DSS effectively supports smartphone selection for ojek online drivers by integrating multicriteria decision-making into a structured system. The model demonstrates reliable ranking results for the evaluated alternatives.
Limitations: The study is limited to four Oppo models and relies on expert-based weighting, which may not fully represent broader driver preferences.
Contributions: This study provides a replicable SMART-based DSS framework for occupational smartphone selection in the gig economy, particularly for improving decision accuracy in driver-oriented technology recommendations.