## 4 Discussion  
The results of this study show that the level and type of noise have a significant relationship with cognitive performance based on the response time and accuracy when doing SCWT cognitive tasks. These results are in line with the studies conducted in [35], which found that noise had a significant effect on the overall outcome of response time and accuracy of cognitive tasks. These results also correspond with the studies of [33], who analyzed the effect of noise on attention and short-term memory, finding that response times to stimuli decreased when noise levels were increased. In contrast to those studies, some studies have found that noise does facilitate performance [70]. One explanation might be that noise can promote arousal and provide excitement for relatively uninteresting occupations, which in turn boosts attention span and task participation. Other studies have found that noise decreases accuracy but speeds up reaction times mostly due to the accuracy-speed tradeoff [71]. An empirical study also found an increase in reaction time (RT) and the number of errors caused by noise exposure [72]. Evidence suggests that noise slows response times for information processing [73]. Another study conducted by [8] found that loud noise exposure significantly reduced attention spans and working memory. Preliminary studies that have been carried out also provide results of level noise factors having a significant effect on the total response time of participants when participants complete the trial-making test [74]. A study by [75] displayed that males have faster RTs than females for both auditory and visual stimuli. EEG is a valuable tool to evaluate cognitive performance based on brain signals and activity patterns [35]. Electroencephalography has certain advantages, which include its being non-invasive, low cost, comfortable, safe, mobile, and having a high time resolution. Therefore, EEG can be a great tool not just for detecting stressors in the environment but also for predicting the negative effects of noise exposure [16]. The analysis of cognitive aspects of attention in this study used the average results of beta power spectrum density signals to measure the cognitive aspects of participants' attention when doing tasks. Beta signals indicate a person's attention is focused on a particular task. The frequency of beta waves is associated with a state of attention and alertness [76]. Based on the type of continuous noise, Figure 6 displays the results of measuring the power spectrum density of the cognitive elements of attention. Participants showed that they had the best attentional conditions at a noise level of 65 dB based on the highest power spectrum log value compared to other noise levels. At the 65 dB level, it is known that the largest power spectrum at the maximum point is at a log power of 39.23 \(\upmu\)V\({}^{2}\) at a frequency of 13.2 Hz. The power spectrum at 65 dB decreases to a minimum of 36.5 \(\upmu\)V\({}^{2}\) at 26.4 Hz. For the intermittent noise type, Figure 6 shows the results of participants having the best attentional conditions. Based on the average log power spectrum, the noise level of 65 dB gives the largest average log power spectrum with the value of 35.01 \(\upmu\)V\({}^{2}\), and the maximum point is at a log power of 37.36 \(\upmu\)V\({}^{2}\) at a frequency of 12.7 Hz. The power spectrum at 65 dB decreased to a minimum of 34.24 \(\upmu\)V\({}^{2}\) at 24.2 Hz. The results of this experiment on the observed beta signals show that the higher the log power spectrum density value and the condition of the lowest frequency value, the more cognitive aspects of participants have the highest attention or concentration. Based on the results of this experiment, continuous noise at a noise level of 80 dB has the highest influence on attention interference, while intermittent noise at a noise level of 85 dB has the highest influence on participants.