Optimization of Goods Tracking and Inventory Systems at PT Integrasi Data Nusantara Using Genetic Algorithms and Functional Testing - Tubagus Adhitya Permana; Fadillah Said; Sri Lestari; Kiki Setyawan (CV. AFDIFAL MAJU BERKAH, 2025)
Inventory management is a critical aspect of business operations, but at PT Integrasi Data Nusantara, the process of determining optimal stock levels and reorder points is still done manually, leading to risks of overstocking or stockouts. This results in high operational costs and potential dissatisfaction among training participants due to a mismatch between supply and dynamic demand. This study aims to optimize the goods tracking and inventory system by using a Genetic Algorithm to address these inefficiencies. The research was conducted at PT Integrasi Data Nusantara using historical training demand data and associated inventory cost data. The methodology includes designing an optimization system, implementing a genetic algorithm with a chromosome structure (ROP, ROQ), a fitness function that minimizes total costs, and evolutionary operators (selection, crossover, mutation). The research results show that the developed system is effective in recommending optimal inventory policies, successfully eliminating all stockout incidents, and significantly improving cost efficiency compared to manual methods. The conclusion of this study is that the implementation of a Genetic Algorithm can be an adaptive and functional solution to support more accurate, efficient, and automated inventory decision-making.