In classical pseudorandom generators (PRNGs), an initial seed is a fundamental requirement to generate a series of random numbers. These generated numbers are intricately tied to the specific seed value used. In digital computation, seed sources are often derived through deterministic processes, which means there is a possibility of using the same seed value deterministically, leading to potential predictability. Conversely, quantum mechanics introduces an inherent randomness that stems from quantum properties such as superposition states, wave-particle duality, and the probabilistic outcomes associated with measurements of quantum superposition states. Leveraging these quantum properties as seed sources represents a promising and convenient avenue, particularly in the context of the post-quantum era. This report is divided into two distinguishable branches. The first segment delves into the impact of seed dependency by employing two well-known PRNG methods. In the subsequent section, we explore how a quantum alternative can serve as a practical and viable solution to address the challenges associated with seed dependency and predictability in the realm of random number generation. This quantum approach uses the inherent randomness in quantum mechanics to enhance the quality and security of random number generation processes.