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All Journal Journal of Computer System and Informatics (JoSYC)
Naufal Rifqi, Muhammad
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Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering

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Sistem Pendukung Keputusan Penentuan Lokasi Pabrik Baru Menggunakan Metode ROC dan MAUT Naufal Rifqi, Muhammad; Tamara Aldisa, Rima
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4893

Abstract

Factories are places where goods and services are mass produced. Factories collect and integrate various resources, such as labor, capital, and machines. Factories have an important role in a country's economy, because they produce goods and services that society needs. Apart from that, factories can also create jobs and improve community welfare. However, factories can also have a negative impact on companies and the environment. Companies that produce goods with certain raw materials must consider the availability of raw materials at the factory location. If raw materials are not available at that location, the company must bring them in from other locations, which can increase production costs. Apart from that, companies must also consider the availability of adequate infrastructure, such as roads, electricity, air and telecommunications. If infrastructure is inadequate, companies have to invest to build it, which can also increase production costs. In this study, the ROC method and the MAUT method were used, the ROC method was used to determine the level of importance of the criteria used in selecting the factory location. The MAUT method is used to rank factory locations. The five criteria used in selecting factory locations are: availability of raw materials, availability of infrastructure, labor costs, transportation costs, and environmental impact. A total of 10 factory locations were selected based on predetermined criteria. The final results show that the best factory location is location E with a final score of 0.682, followed by location H and location F with a final score of 0.619 and 0.453 respectively.
Co-Authors Tamara Aldisa, Rima