The application of machine learning in solving inventory management problem
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Institusion
Universitas Katolik Widya Mandala Surabaya
Author
Emmanuela Maria Jessica Setyawan (STUDENT ID : jessiset0710@gmail.com)
Wahyudi Wibowo (LECTURER ID : 0715047402)
Wahyudi Wibowo (LECTURER ID : 0715047402)
Subject
Business
Datestamp
2021-08-31 01:47:36
Abstract :
Inventory is an investment and a potential source of waste that needs to be carefully controlled. Frequent changes and new events which occur in the market create another challenge for forecasting. This makes the Small and Medium Industry (SMI) who plan production not totally sure that the prepared prognoses will come true 100%. This is where machine learning comes into play. Artificial intelligence needs to be teamed with human oversight and should be treated as part of the system but not as a replacement for the system or the system itself. This research aims to develop a machine learning model for inventory management of Small and Medium Industry (IKM) based on demand prediction. To achieve the purpose of the study, the study uses descriptive methods. The result is an application called Managerku. The demand prediction shows that it captures the seasonality of the data. In this research, we will discuss the challenges of building an application using machine learning for inventory management problems.
Inventory is an investment and a potential source of waste that needs to be carefully controlled. Frequent changes and new events which occur in the market create another challenge for forecasting. This makes the Small and Medium Industry (SMI) who plan production not totally sure that the prepared prognoses will come true 100%. This is where machine learning comes into play. Artificial intelligence needs to be teamed with human oversight and should be treated as part of the system but not as a replacement for the system or the system itself. This research aims to develop a machine learning model for inventory management of Small and Medium Industry (IKM) based on demand prediction. To achieve the purpose of the study, the study uses descriptive methods. The result is an application called Managerku. The demand prediction shows that it captures the seasonality of the data. In this research, we will discuss the challenges of building an application using machine learning for inventory management problems.
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ABSTRAK - Emmanuela Maria Jessica Setyawan.pdf
BAB 1 - Emmanuela Maria Jessica Setyawan.pdf
BAB 2 - Emmanuela Maria Jessica Setyawan.pdf
BAB 3 - Emmanuela Maria Jessica Setyawan.pdf
BAB 4 - Emmanuela Maria Jessica Setyawan.pdf
BAB 5 - Emmanuela Maria Jessica Setyawan.pdf
LAMPIRAN - Emmanuela Maria Jessica Setyawan.pdf
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