Prediction of Dental Prosthesis Material Stock Using the K-Means Algorithm (Case Study: Hijrah Dental Lab)

Authors

  • Devi Selvi Yanti Informatics Engineering Study Program, Faculty of Engineering, Universitas Pahlawan Tuanku Tambusai, Indonesia
  • Hidayati Rusnedy Informatics Engineering Study Program, Faculty of Engineering, Universitas Pahlawan Tuanku Tambusai, Indonesia
  • Hanantatur Adeswastoto Civil Engineering Study Program, Faculty of Engineering, Universitas Pahlawan Tuanku Tambusai, Indonesia

DOI:

https://doi.org/10.31004/jestm.v6i3.390

Keywords:

K-Means Clustering, Stock Prediction, System Design, Waterfall Method

Abstract

Issues of excess and shortage of denture materials at Hijrah Dental Lab still occur frequently due to manual inventory management, leading to delays in denture production services. This study aims to analyze usage patterns and predict stock requirements using the K-means algorithm based on 180 order data records from 2022–2024. The clustering process produced three groups: C1 (high demand, 75 records) dominated by Acrylic and Vertex Thermosens materials; C2 (medium demand, 33 records) including Valplast and Acrylic Retainer; and C3 (low demand, 72 records) dominated by Crown materials such as PFM, Emax, and Zirconia The prediction results show that materials in the high cluster have low monthly usage, making their stock relatively stable. The medium cluster can be managed based on actual needs, while the low cluster requires closer monitoring due to higher usage. The K-Means algorithm helps make stock managementmore effective and timely.

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Published

2026-10-30

How to Cite

Selvi Yanti, D., Rusnedy, H., & Adeswastoto, H. (2026). Prediction of Dental Prosthesis Material Stock Using the K-Means Algorithm (Case Study: Hijrah Dental Lab). Journal of Engineering Science and Technology Management (JES-TM), 6(3), 733–740. https://doi.org/10.31004/jestm.v6i3.390

Issue

Vol. 6 No. 3 (2026): September-November 2026

Section

Articles

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Copyright (c) 2026 Devi Selvi Yanti, Hidayati Rusnedy, Hanantatur Adeswastoto

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