Bin packing is an optimization problem defined as placing different sized objects into similar containers or bins to minimize the number of used bins. This problem has different variations based on the dimensions of the bins, placement limitations, and priority. This paper focuses on one-dimensional bin packing. Two algorithms are explored in this paper, which are First Fit, First Fit Decreasing. The contribution of the paper is to explore the effect of parallelization on the First Fit Decreasing algorithm regarding the processing time and the utilization rate. Furthermore, the effect of using different numbers of concurrent workers on the problem is also explored. We proved that just by parallelizing the sorting in the First Fit Decreasing algorithm, we can decrease the computation time by 4.73% without affecting the utilization rate.