Cloud computing is a relatively new way of utilizing online resources, and it's growing increasingly popular. The cloud could have very strong traffic at times and very low traffic at other times. Scheduling algorithms are essential to the process. The cloud computing issue is affected by causative factors, such as execution time, end time, waiting, and average waiting. However, the number of jobs in cloud environments is effectively impacted by the algorithms' higher latency and rapid response times. The research aims to improve the accuracy of task finishing time and waiting time by minimizing waiting time and execution times. The algorithms were elaborated, compared, and evaluated in terms of execution time, end time, waiting time, and average waiting time. The dataset was coded using the Java programming language and inserted into the simulation tools. The result was achieved in terms of execution time, completion time, and waiting time using the simulation tool Cloudsim in the comparison program, the Eclipse program. Compare the average waiting time between the SJF, FCFS, and RR algorithms. The SJF algorithm has the lowest rate, rather than Findings also proved that the SJF algorithm was the most effective over other alternative algorithms.