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All Journal Journal of Energy, Material, and Instrumentation Technology
Muhammad, Riki
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Control & Systems Engineering Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics

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Development of a Portable Low-Cost Multispectral Sensor Integrated with IoT and Machine Learning for Classifying Honey Types Muhammad, Riki; Isroni; wisesa, Tri Pujian; Syahputra, Tri Siswandi
Journal of Energy, Material, and Instrumentation Technology Vol 6 No 3 (2025): Journal of Energy, Material, and Instrumentation Technology
Publisher : Departement of Physics, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jemit.343

Abstract

Accurate honey type authentication is a significant challenge for small-scale producers, as conventional methods are often costly and impractical. This study aims to design and develop a low-cost honey classification prototype by integrating the AS7265X multispectral sensor with Internet of Things (IoT) technology and machine learning. Spectral data from 18 channels of various Indonesian honey types were acquired using the AS7265X sensor and analyzed exploratively using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). The data were then normalized and used to train Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) classification models. An ESP32-based IoT system was developed for real-time monitoring and cloud data storage. The results demonstrate that AS7265X spectral data effectively differentiate honey types, with the ANN model achieving 94.05% accuracy, supported by a responsive IoT system (1–2 seconds) for monitoring and centralized storage. This prototype shows potential as a practical, rapid, accurate, and efficient honey authentication solution for various stakeholders.
Co-Authors Isroni Syahputra, Tri Siswandi wisesa, Tri Pujian