<![CDATA[Processing large data sequentially is often inefficient and time-consuming. Parallel computing is a fundamental solution to accelerate computation by dividing tasks among multiple processing units. This research aims to analyze the influence of the number of processes on the performance of parallel computing implemented using the `fork()` system call on the Linux operating system. A C program was developed to perform a CPU-intensive task on a stock price dataset. Testing was conducted with varying numbers of processes: 1, 2, 4, and 8. The performance metrics measured were wall time, speedup, and efficiency. The test results show a significant reduction in execution time as the number of processes increases. The system achieved near-linear speedup (2.00x for 2 processes, 4.00x for 4 processes, and 7.93x for 8 processes) with high efficiency (99%). These findings prove that the `fork()`-based multi-process approach is highly effective for CPU-bound tasks.]]>
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