Journal of Engineering, Project, and Production Management, 2026, 16(5), 2025-59
Augmented Reality-Supported Fuzzy Multi-Criteria Decision Making for Photovoltaic System Optimization
1 Associate
Professor, Faculty of Engineering; Senior Lecturer, Department of
Electrical Engineering, Universitas Negeri Surabaya, East Java,
Indonesia, E-mail: unitthree@unesa.ac.id (corresponding author).
2 Associate Professor, Faculty of
Engineering; Senior Lecturer, Department of Education Technology,
Universitas Negeri Surabaya, East Java, Indonesia, E-mail: fajararianto@unesa.ac.id
3 Associate Professor, Faculty of
Engineering; Senior Lecturer, Department of Mechanical Engineering,
Universitas Negeri Surabaya, East Java, Indonesia, E-mail:
priyoheruadiwibowo@unesa.ac.id
Project Management
Received March 31, 2025; revised October 28, 2025; October 31, 2025; December 31, 2025; accepted April 23, 2026
Available online June 17, 2026
Abstract: This paper models and evaluates the use of Augmented Reality technology, supported by the decision-making process, for modeling Photovoltaic system generation. Specifically, for the optimization of very short-term solar irradiance forecasting one hour ahead, with the recommended combination modeling design based on meteorological data, as well as the main data, namely the optimization of power generation operations of photovoltaic (PV) generation systems. This paper proposes an Augmented Reality (AR)-supported Multi-Criteria Decision-Making (MCDM) approach to simplify and improve the fuzzy decision-making process. The hybrid method is the first in theory of Fuzzy-Multi-Criteria Decision-Making, which combines Augmented Reality with Fuzzy-Multi-Criteria Decision-Making-Neural Networks (AR-F-MCDM-NN), using the main support for virtual environment decision-making. Specifically, the Augmented Reality model provides better visual information than other visual models, turning complex decision methods into easy-to-use tools, especially for modeling photovoltaic (PV) generation systems. A mathematical model is used to design a PV generation system to optimize Global Horizontal Irradiance (GHI) forecasting one hour ahead. In calculating the error value in the hybrid method, a Mean Absolute Percentage Error (MAPE) value of approximately 5.6% was obtained. The results of the combination model simulation were then compared with real data, and the training test results showed that the combination model proposed in this study could calculate SI with high validity and results consistent with the actual data.
Keywords: Photovoltaic system, augmented reality, decision making, solar irradiance, forecasting, asynchronous collaborative.
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Citation: Kartini, U. T., Arianto, F., and Adiwibowo, P. H. (2026). Augmented Reality-Supported Fuzzy Multi-Criteria Decision Making for Photovoltaic System Optimization. Journal of Engineering, Project, and Production Management, 16(5), 2025-59.
