<![CDATA[The rapid advancement of digital technology today is having an impact on various aspects of life. One of these aspects is transportation. Tech-based startups have emerged and are competing fiercely through various means, such as offering promotions or providing the best services for both users and drivers. The emergence of online motorbike taxi applications (ojol) has provided drivers with many options but has also created a problem: choosing the best application to use. Ojol applications have their pros and cons, such as differences in daily earnings, the number of or-ders, application commissions, bonuses, and driver satisfaction. Furthermore, conditions on the ground are dynamic, and these factors can change at any time depending on the region, time, and company policies. Given these challenges, drivers need a decision support system (DSS) to help them choose the best motorbike taxi applications for optimal decision-making so they can make optimal decisions. The research involved 30 drivers (respondents). It was conducted using a quan-titative method with a DSS approach that combined the AHP and MOORA methods. The AHP method was used to determine the weights of the criteria based on their level of importance. The MOORA method was applied to rank the alternatives. The results of the study, which used the AHP-MOORA hybrid method, show that Gojek ranks first among the recommended motorbike taxi applications that drivers can choose from, with the highest Yi value of 0.434975.. It is hoped that based on existing mathematical analysis, drivers can determine the best and most optimal de-cisions from several alternative motorbike taxi applications.]]>
