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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications
Edi Abdurachman
Bina Nusantara University
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Mathematics

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Machine learning in drug supply chain management during disease outbreaks: a systematic review Gunadi Emmanuel; Arief Ramadhan; Muhammad Zarlis; Edi Abdurachman; Agung Trisetyarso
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5517-5533

Abstract

The drug supply chain is inherently complex. The challenge is not only the number of stakeholders and the supply chain from producers to users but also production and demand gaps. Downstream, drug demand is related to the type of disease outbreak. This study identifies the correlation between drug supply chain management and the use of predictive parameters in research on the spread of disease, especially with machine learning methods in the last five years. Using the Publish or Perish 8 application, there are 71 articles that meet the inclusion criteria and keyword search requirements according to Kitchenham's systematic review methodology. The findings can be grouped into three broad groupings of disease outbreaks, each of which uses machine learning algorithms to predict the spread of disease outbreaks. The use of parameters for prediction with machine learning has a correlation with drug supply management in the coronavirus disease case. The area of drug supply risk management has not been heavily involved in the prediction of disease outbreaks.
Co-Authors Achmad Imam Kistijantoro Agung Trisetyarso Agustinus Bandur Antoine Doucet Antoni Wibowo Arief Ramadhan Boy Subirosa Sabarguna David David Erick Fernando Farid Bintoro Aji Ford Lumban Gaol Gunadi Emmanuel Ivan Sebastian Edbert Meyliana Meyliana Mochammad Haldi Widianto Muhamad Keenan Ario Muhammad Zarlis Priati Assiroj Rakhmat Arianto Ridha Sefina Samosir Sunardi Sunardi Suryadiputra Liawatimena Warnars, Harco Leslie Hendric Spits Wibowo Kosasih Yaya Heryadi