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All Journal JISI UMJ (Jurnal Integrasi Sistem Industri UMJ) journal of Renewable Engineering
Boru Butar Butar, Maulida
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Industrial & Manufacturing Engineering

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Determining Book Distribution Routes by Implementing Vehicle Routing Problems Using Excel Solver at Gunadarma University Boru Butar Butar, Maulida; Medikano, Alsen; Zulkarnain, Yahya
Journal of Renewable Engineering Vol. 1 No. 4 (2024): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/dt01s735

Abstract

Gunadarma University operates multiple campuses, each equipped with its own library. To ensure equitable access to newly acquired titles, it is imperative that these materials are disseminated across all campus libraries. So, when a new book title is added, this book must also be owned by the library at each campus location. In this research, book distribution routes with the shortest distance and time will be determined using the Vehicle Routing Problem (VRP) method with Excel Solver. Gunadarma University has a central library which is the starting point for distributing books to other campuses. The central university library serves as the distribution hub, from which books are dispatched to seven additional campus locations. Simulation results using Excel Solver showed that the shortest route for sending books to seven library locations on the Gunadarma University campus using one vehicle was a distance of 137.14 km in 3 hours 12 minutes. This optimized route yielded substantial cost savings, amounting to a 12.5% reduction compared to previous distribution practices.  
PEMILIHAN PEMASOK MENGGUNAKAN METODE K-MEANS KLUSTERING BERBASIS PYTHON Zaen, Miftakhul; Boru Butar Butar, Maulida; Nasution, Syarifuddin; Mohamad Noor, Asep
JISI: Jurnal Integrasi Sistem Industri Vol. 12 No. 1 (2025): JISI UMJ
Publisher : Fakultas teknik Universitas Muhammadiyah Jakarta

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Abstract

Supplier selection is a decision-making process that is complex and carries a lot of risks. Therefore, in order to make decisions more precise, decision-making requires tools that are scientific, logical and structured. Currently, most supplier selection is done using manual calculations, so it requires accuracy in doing so. With current technological advances supplier selection can be implemented with artificial intelligence. Implementing artificial intelligence by selecting suppliers can reduce errors in manual calculations and hopefully get better suppliers. The purpose of this research is to implement artificial intelligence into supplier selection with the method used, namely K-means clustering with the criteria used are quality, price, and delivery time. The data used in this research is secondary data sourced from Kaggle so the weight of each criterion is unknown. The results of this study show that the best suppliers are supplier 19 in cluster 0, supplier 8 in cluster 1, and supplier 20 in cluster 3.
Co-Authors Alsen Medikano Mohamad Noor, Asep Syarifuddin Nasution, Syarifuddin Zaen, Miftakhul Zulkarnain, Yahya