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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Sofyan Wahyudi
Bina Nusantara University
Computer Science & IT

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Evaluation Of Supply Chain Management In Heavy Equipment Industry Using Artificial Neural Network Sofyan Wahyudi
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 10 No 2 (2023): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v10i2.5320

Abstract

In relation to the increase in coal prices worldwide in the post Covid-19 pandemic, the heavy equipment business in Indonesia has had a positive impact, one of which is the heavy equipment spare part business. It is very important for the company to maintain the supply of goods to satisfy customers, therefore supply chain management is essential to be evaluated. The aim of this study is to prove that Artificial Neural Network can be applied to assess the supply chain performance of a heavy equipment spare part company. This study will collect data from a holding company in the heavy equipment spare part business located in Jakarta, which will provide an assessment of supply chain performance to all of its subsidiaries located in Jakarta. The research method will use Artificial Neural Network and its accuracy is proven with a confusion matrix. This research to prove that Artificial Neural Network for supply chain performance assessment of heavy equipment spare part companies that has never been done by previous research. The main results from this research are Artificial Neural Network can be applied to measure supply chain performance of heavy equipment spare part companies. State a brief limitation of the study is only limited to spare part companies under PT. XYZ. This study can provide a contribution to Supply Chain Management and Operation Management in the field of heavy equipment.
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