Analisa Penjadwalan Order Distribusi Produk di PT. Indofood CBP Sukses Makmur Medan Menggunakan Algoritma Genetika


  • Lisa Febriani Universitas Labuhan Batu
  • Iwan Purnama Universitas Labuhan Batu
  • Budianto Bangun Universitas Labuhan Batu



Genetika, Penjadwalan, Distribusi


The existence of computers has even replaced many human workers, both in business and industry. This cannot be faulted because it is proven that the computerized system is much more efficient and profitable for the company than the manual system (with human labor). Almost every company, especially those that are developing and advancing, are currently competing to computerize their company's systems, to improve work efficiency and effectiveness. At PT. Indofood CBP Sukses Makmur Medan, especially those that produce goods, always occurs in the process of producing, storing, and selling products. With the application design carried out in the making of this research is the storage of input and output of data from existing goods, namely by managing all data on goods in the warehouse in a computerized system. Then the arrangement of incoming goods and outgoing goods in the warehouse rack pallets is arranged as optimally as possible by using the Genetic Algorithm method. The scheduling at PT. Indofood CBP Sukses Makmur Medan, which is a schedule of orders given to sales that can be on that day. Next, distribution orders are scheduled on the day, hour, and sales working. In optimizing the preparation of the distribution order schedule using the genetic algorithm, four parameters are needed, including the number of goals, the number of sales, the order crossover and mutation probability. In designing a product distribution order scheduling system at PT. Indofood CBP Sukses Makmur Medan consists of a login form, order data, sales data, destination data, time data, genetic algorithm processing and logout.


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How to Cite

Febriani, L., Purnama, I., & Bangun, B. (2021). Analisa Penjadwalan Order Distribusi Produk di PT. Indofood CBP Sukses Makmur Medan Menggunakan Algoritma Genetika. MEANS (Media Informasi Analisa Dan Sistem), 6(1), 84–89.



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