<![CDATA[Choosing the right smartphone is a challenge amidst the variety of options available in the market. To overcome this problem, a decision support system is needed that can help consumers in determining the best choice based on various criteria. This research aims to design a smartphone selection decision support system using the Multi-Objective Border Approximation Area Comparison (MABAC) method. The MABAC method was chosen because of its ability to handle various complex and conflicting criteria, such as price, features, camera quality, battery life, performance, and design. The system designed in this study integrates data from various trusted sources, such as user reviews, technical specifications, and product ratings from reputable technology sites. The collected data is then processed using the MABAC algorithm to give a final score to each available smartphone alternative. This process involves several stages, including data normalization, determination of criteria weights, and calculation of the final score for each alternative. The results of this system implementation show that the MABAC method can provide smartphone recommendations that match user preferences and needs more objectively and accurately. Users can enter their preferences regarding the weight of criteria that are considered important, and the system will provide the best smartphone recommendations based on these preferences. Thus, this decision support system is expected to help consumers make more effective and efficient decisions, and reduce uncertainty in the smartphone selection process.]]>
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