PT. XYZ is a manufacturing industry company engaged in drinking water, this company still has problems in its distribution, the existence of undirected shipping or waste of transportation distribution costs for shipping in several regions because shipping in the area uses only one vehicle at each destination resulting in delivery distance getting longer. Therefore, this research was conducted to improve distribution costs using the saving matrix method and the nearest neighbor algorithm. The results of the company's distribution costs are Rp. 18,940,924 / month after using this method the distribution cost becomes Rp. 16,302,392 / month and with the saving matrix method and the nearest neighbor algorithm, it saves 16% of the cost proposed by the company.PT. XYZ adalah perusahaan industri manufaktur yang bergerak dibidang air minum, perusahaan ini masih terdapat permasalahan dalam distribusinya, adanya pengiriman yang tidak terarah atau pemborosan biaya distribusi transportasi untuk pengiriman beberapa daerah dikarnakan pengiriman di daerah tersebut hanya menggunakan satu kendaraan pada masing masing tujuan yang mengakibatkan jarak pengiriman semakin panjang. Sebab itu penelitian ini dilakukan guna memperbaiki biaya distribusinya menggunakan metode saving matrix dan algoritma nearest neighbor. Hasil biaya distribusi perusahaan yaitu Rp. 18.940.924 / bulan setelah menggunakan metode tersebut biaya distribusinya menjadi Rp. 16.302.392 / bulan serta dengan metode saving matrix dan algoritma nearest neighbor jadi lebih menghemat 16% dari biaya yang diusulkan dari perusahaan.
PT. XYZ is a business entity engaged in the production of mineral water. In the distribution process, the company still has an obstacle that is an unstructured shipping scheme that causes waste of transportation costs in some areas. This problem is caused by limited vehicle facilities so that the distance traveled for delivery of goods is longer. This study uses Saving Matrix method and nearest neighbor algorithm calculation of the phenomenon, this research was conducted to analyze distribution costs to be more efficient. neighbor. The result of this study is the company's distribution cost data of Rp. 18,940,924/month after done the cost of distribution into and with saving matrix method and Nearest Neighbor algorithm so save 16% which is Rp. 16.302.392 / month from the initial cost proposed from the company.PT. XYZ meruapakan sebuah badan usaha yang bergerak di bidang produksi air mineral. Di dalam proses distribusinya, perusahaan ini masih memiliki sebuah kendala yaitu skema pengiriman yang tidak terstruktur yang menyebabkan pemborosan biaya transportasi di beberapa daerah. Permasalahan ini di sebabkan oleh fasilitas kendaraan yang terbatas sehingga jarak yang ditempuh untuk pengiriman barang semakin panjang. Penelitian ini menggunakan metode Saving Matrix dan perhitungan algoritma Nearest Neighbor Dari fenomena tersebut, penelitian ini dilakukan untuk melakukan analisa biaya distribusi agar lebih efrisien. neighbor. Hasil dari penelitian ini adalah data biaya distribusi perusahaan sebesar Rp. 18.940.924/bulan setelah dilakukan biaya distribusinya menjadi serta dengan metode Saving Matrix dan algoritma Nearest Neighbor jadi lebih menghemat 16% yaitu sebesar Rp. 16.302.392 / bulan dari biaya awal yang diusulkan dari perusahaan.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.