SISTEM PENCARIAN RUTE TERBAIK EKSPEDISI BARANG MENGGUNAKAN METODE ANT COLONY PADA PT. PELINDO TPKNM

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Published Apr 18, 2024
https://doi.org/10.56708/progres.v16i1.388
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Vol 16 No 1 (2024): April

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Muhammad Rahmat Faizal
Program Studi Sistem Informasi, STMIK Profesional Makassar
Kasirun Sitorus
Program Studi Sistem Informasi, STMIK Profesional Makassar
Mika Tandililing
Program Studi Sistem Informasi, STMIK Profesional Makassar
Suardi Hi Baharuddin
Program Studi Sistem Informasi, STMIK Profesional Makassar

Abstract

This research is focused on building and implementing a system for finding the best route in cargo expeditions for PT. Pelindo. PT. Pelindo faces a significant challenge in providing the best service to its customers to enhance their satisfaction. In response to this challenge, the developed system employs the Ant Colony Optimization (ACO) approach, inspired by the foraging behavior of ants when searching for the shortest path from their nest to a food source. Through ACO, the system aims to provide optimal and efficient route solutions.


The research results encompass the development and implementation of ACO calculations within a system capable of generating the best alternative routes. The routes generated involve eight main points, namely A-B-C-D-E-F-G-H-A. It is expected that this system will be a highly valuable tool for users in finding the most efficient and cost-effective travel routes for cargo expeditions. Furthermore, the outcomes of this research are anticipated to contribute positively to improving the quality of service provided by PT. Pelindo to their customers, thus enhancing customer satisfaction and overall logistics operational efficiency.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Faizal, M. R., Sitorus, K., Tandililing, M., & Baharuddin, S. H. (2024). SISTEM PENCARIAN RUTE TERBAIK EKSPEDISI BARANG MENGGUNAKAN METODE ANT COLONY PADA PT. PELINDO TPKNM. Jurnal Informatika Progres, 16(1), 1-8. https://doi.org/10.56708/progres.v16i1.388

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