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All Journal Industrial Innovation
Gilang Fatikhul Burhan
Politeknik ATK Yogyakarta

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Modeling of women shoes sizing system based on 3D foot scanner result using machine learning approach Jamila Jamila; Eka Legya Frannita; Gilang Fatikhul Burhan; Windra Bangun Nuswantoro; Anwar Hidayat; Erlita Pramitaningrum; Totok Yulaidin
Industrial Innovation Vol. 2 No. 2 (2025): Industrial Innovation
Publisher : Politeknik ATK Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58533/aqn1f925

Abstract

Accurate shoe sizing plays a crucial role in ensuring comfort, performance, and consumer satisfaction, particularly for women whose foot shapes exhibit considerable anatomical variability. To address this challenge, this research proposes a data-driven modeling framework for developing a women’s shoe sizing system based on three-dimensional foot scanner data. The study was carried out through a systematic process consisting of data preprocessing, clustering using the K-Means algorithm, and evaluation of the clustering performance. The clustering analysis identified four optimal clusters within the dataset, representing distinct patterns in foot dimension measurements. The evaluation result, with a Silhouette Score of 0.25, indicates a moderate yet acceptable level of cohesion and separation among the clusters. These findings demonstrate that the proposed model can effectively capture the underlying structure of women’s foot morphology, providing a scientific foundation for establishing more accurate, customized, and ergonomically appropriate shoe sizing standards.
Co-Authors Anwar Hidayat Eka Legya Frannita Jamila Jamila Pramitaningrum, Erlita Pramitaningrum Totok Yulaidin Windra Bangun Nuswantoro