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All Journal Indonesian Journal of Information System Journal of Advanced in Information and Industrial Technology (JAIIT)
Curie Habiba
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Development of Foot Mat Sensor Technology for Foot Identification and BMI-Based Biomechanical Risk Prediction Evanita; Slamet Khoeron; Andre Tri Saputra; Curie Habiba
Indonesian Journal of Information Systems Vol. 8 No. 1 (2025): August 2025
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i1.11505

Abstract

This study advances the Foot Mat Sensor (FMS) technology to discern foot morphology and forecast biomechanical vulnerabilities predicated on Body Mass Index (BMI). The proposed system amalgamates the analysis of plantar pressure with various biomechanical parameters, including heel pressure, midfoot pressure, forefoot pressure, and foot contact area (FCA). Data were collected from ten participants exhibiting a spectrum of BMI, foot morphology (High Arch, Normal Arch, and Low Arch), foot length, contact area, and asymmetrical plantar pressure. The findings indicated a statistically significant correlation between elevated BMI (>25), irregular plantar pressure distribution, and heightened biomechanical risk. Participants with high BMI and Low Arch (LA) foot morphology demonstrated an augmented risk, with plantar pressure asymmetry ≥20 kPa as the principal indicator. The prediction model founded on the Random Forest algorithm attained an accuracy of 85% in categorizing biomechanical risk into low, medium, and high classifications. The Digital Footprint Scanner technology, innovated through this research, is anticipated to augment the efficacy of personalized and precise diagnostics and the prophylaxis of biomechanical injuries. This endeavor contributes to formulating a data-driven system for the early detection of biomechanical risks, with applications in medicine, athletics, and rehabilitation.
Exploring Logistics Process Improvement Possibility with SCOR Digital Standard and Lean Waste Analysis Adhie Prayogo; Curie Habiba; Ulkhaq, M. Mujiya; Dina Tauhida; Sitompul, Fachri Rizky
Journal of Advances in Information and Industrial Technology Vol. 7 No. 2 (2025): Nov
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v7i2.723

Abstract

Inbound logistics, including receiving goods, quality and physical checking, item inquiry, and stock-level checking are essential aspects within supply chain management in which the unresponsive operation may lead to inefficiency. This study aims to observed the ongoing operations in a mid-sized paper manufacturer using a combination of Business Process Modelling to map the current flow process, Lean Waste Analysis to identify possible wastes, and SCOR Digital Standard to offer improvement opportunities. The results show that waiting, motion, overprocessing, and inventory wastes are identified across the three logistics main processes. Additional waste, human skill, is observed in the stock-level checking procedure. Subsequently, SCOR DS recommends the firm to escalate the human skills of lean manufacturing, bar code handling & RFID, ERP system, automation tool, time management, and collaboration, to support the performance improvement. Finally, the study proposed metrics within four dimensions to validate the solution impact on the performance, including the responsiveness, reliability, asset management, and people.
Co-Authors Adhie Prayogo Andre Tri Saputra Dina Tauhida Evanita M. Mujiya Ulkhaq Sitompul, Fachri Rizky Slamet Khoeron