The difference between a random error and a systematic error is small and could be a little confusing at first glance. Some students assume that random error is things like a gust of wind effecting the experimental set up. That is not the case. That gust of wind might eventually cause a random error, but maybe not. Both systematic and random experimental errors refer to problems associated with taking measurements.
A random error is caused by changes in the measured data. The cause of this is likely the precision limitations of what you are measuring with. For example using only a meter stick to measure the length of a person's stride. There is guaranteed to be some variation in the measurements because the tool isn't accurate enough. I see this kind of thing in my science classes where students will measure the mass of an object several times and get slightly different mass measurements each time. 20.23 g, 20.27 g, and 20.19 g. Same object, same balance, different measurements. Those are random. Any of the balances used in your experimental set up could create these kinds of errors. The way to minimize random error is to take more data. More data means more accurate data and the ability to take and use averages.
A systematic error, on the other hand, are generally reproducible errors. They are generally all in the same direction of measurement, and they are often present throughout the entire experiment. I see that you are using an electronic scale at one point. If it is not correctly zeroed out (tare) then it will cause all of your measurements to read too high (or too low) every single time. Your multimeter might have the same issue. This kind of error is difficult to detect because it is consistent throughout the experiment. Probably the best way to compensate for it is to initially compare the measurements from several different measuring tools. If they all read the same, you are good to go.