Measuring the Situational Awareness when Driving on Online Motorcycle Taxi Drivers in an Efforts to Reduce Work Accidents Using the QUASA Method

Abstract

The increasing demand for online motorcycle taxi services has been followed by an increase in traffic accidents. According to data from the Indonesian National Police, an average of 3 people die every hour due to traffic accidents and 61% of these accidents are caused by human factors such as the ability and character of the driver. Seeing the many cases that have occurred, in this study it is necessary to analyze the level of alertness of online motorcycle taxi riders with the aim of knowing the level of alertness of online motorcycle taxi riders so as to reduce the accident rate using the Quantitative Analysis Of Situational Awareness (QUASA) method. The results showed that the characteristics of online motorcycle taxi drivers are over confident. Based on the calculation, the level of alertness is 34.94%, the hit rate value is 0.617 and the false alarm rate is 0.498, the sensitivity value of 0.29 and the bias value of-0.135. The conclusion is that online Grab motorcycle taxi drivers tend to be less alert and overly confident so that they endanger themselves, their passengers and road users.