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All Journal Journal of Energy, Material, and Instrumentation Technology Jurnal Informatika Ekonomi Bisnis
Isroni
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Control & Systems Engineering Economics, Econometrics & Finance 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.
Leveraging Digital Transformation for Sustainable Competitive Advantage in Emerging Markets: A Managerial Perspective Suharyadi, Dedi; Adhi, Sukmono Bayu; Isroni; Irawan, Roy
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 4 (December 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i4.1294

Abstract

Digital transformation has emerged as a critical catalyst for achieving competitive advantage in the knowledge-based economy. This study aims to examine the role of managerial capability in driving digital transformation success and its impact on sustainable competitive advantage among firms operating in emerging markets. Employing a quantitative explanatory survey design, data were collected from 150 respondents consisting of mid and senior level managers in the manufacturing, service, and financial sectors across Indonesia, Malaysia, and Vietnam. The data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0. The results reveal that managerial capability significantly influences digital transformation, which in turn positively affects firms’ dynamic capabilities. Moreover, dynamic capabilities were found to mediate the relationship between digital transformation and sustainable competitive advantage. The institutional context also moderates this relationship, suggesting that regulatory and normative support enhances strategic innovation. These findings highlight that the synergy between managerial vision, digital adoption, and organizational adaptability constitutes the foundation of long-term competitiveness in emerging markets. The study enriches digital strategy literature and offers practical implications for managers and policymakers aiming to foster sustainable digital ecosystems.
Co-Authors Karlina, Eulin Muhammad, Riki Roy Irawan Sukmono Bayu Adhi Syahputra, Tri Siswandi wisesa, Tri Pujian