Published: 2023-12-30
Classification of Production Machine Spare Part Stock Data Request Needs Using The K-Nearest Neighbor Method
DOI: 10.35870/ijsecs.v3i3.1878
Abstract
Spare parts encompass various items that are offered, owned, utilized, or consumed to fulfill consumer desires and requirements. This research implements the K-Nearest Neighbor algorithm on a test dataset consisting of 100 data objects, resulting in a novel classification perspective. The study includes a comprehensive model evaluation process involving Cross Validation on both training and testing datasets, comprising 1000 records with 36 critical and 64 non-critical outcomes. Performance assessment and testing utilizing the RapidMiner Studio application yield optimal results under various modeled scenarios. The accuracy of this algorithm model stands at 98.00%, with a standard deviation of +/- 4.00%.
Keywords
Spare Parts; Machinery; Products; Data Mining; K-NN; Classification
Article Information
This article has been peer-reviewed and published in the International Journal Software Engineering and Computer Science (IJSECS). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
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Issue: Vol. 3 No. 3 (2023)
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Section: Articles
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Published: 2023-12-30
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License: CC BY 4.0
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Copyright: © 2023 Authors
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DOI: 10.35870/ijsecs.v3i3.1878
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Hamdi Yansyah, Universitas Pelita Bangsa Cikarang
Informatics Engineering Study Program, Faculty of Engineering, Universitas Pelita Bangsa Cikarang, Bekasi Regency, West Java Province, Indonesia
Sifa Fauziah, Universitas Pelita Bangsa Cikarang
Informatics Engineering Study Program, Faculty of Engineering, Universitas Pelita Bangsa Cikarang, Bekasi Regency, West Java Province, Indonesia
Donny Maulana, Universitas Pelita Bangsa Cikarang
Informatics Engineering Study Program, Faculty of Engineering, Universitas Pelita Bangsa Cikarang, Bekasi Regency, West Java Province, Indonesia
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