Pengaruh Tingkat Beban Kerja Mental terhadap Kinerja Driver Bike X Medan

Abstract

Drivers are the spearhead of ride hailing companies. However, many X Bike Drivers complain because Drivers' income is considered to be increasingly inadequate due to the high deductions that must be paid by X Bike Drivers to the company. As a result, to fulfill income, X Bike Drivers have to work harder and of course the perceived mental workload also increases, which is expected to affect the performance of these Drivers. Using the NASA-TLX method, the mental workload of 100 X Bike Drivers in Medan was measured. And the performance will be measured so that a linear regression analysis can be carried out to determine the effect of mental workload on the performance of X Bike Drivers. Measurement of mental workload is carried out using 6 indicators, namely mental needs, physical needs, time requirements, performance, effort, and frustration levels. Meanwhile, performance is measured by indicators of the level of completion of orders and the average Driver rating. The measurement results were obtained from 100 X Bike Drivers, 92 people (92%) experienced moderate category mental workload, and 8 people (8%) experienced rather high category mental workload. As well as the performance of Drivers classified as Very Good as many as 12 people (12 %), Good as many as 34 people (34%), Somewhat Good as many as 28 people (28%), Somewhat Bad as many as 19 people (19%), Bad as many as 7 people (7%). After the linear regression test was carried out, the path coefficient (R) was 0,606 which indicated the strength of the relationship between mental workload and performance in this study was strong in a positive direction. And the R Square value of 0,376 means that 36,7% mental workload affects the performance of X Bike Drivers. Then the coefficients are calculated and the constant value (a) is 81,434 and the coefficient value (b) is 0,295, so the resulting regression equation is: Y = 81,434 + 0,295 X. Next, using RapidMiner, clustering the mental workload and performance of X Bike Drivers is done to find out optimal mental workload value for X Bike Drivers so that their performance is good.