PEMANFAATAN AUGMENTED REALITY DAN MACHINE LEARNING UNTUK EDUKASI DAN PEMANTAUAN KEBERSIHAN DESTINASI WISATA
Abstract
The tourism sector plays a strategic role in national economic development; however, environmental cleanliness at tourism destinations remains a persistent challenge that affects destination quality, visitor experience, and sustainability. This study aims to support the Clean Tourism Movement (Gerakan Wisata Bersih) by developing an application that utilizes Augmented Reality (AR) for environmental cleanliness education and Machine Learning (ML) for destination cleanliness monitoring. AR is employed as an interactive visual medium to enhance tourists’ and local communities’ awareness of clean tourism practices, while ML is applied to analyze image-based data to support automated cleanliness monitoring. The study adopts a Research and Development (R&D) approach using the ADDIE model, encompassing analysis, design, development, implementation, and evaluation stages. Data were collected through observation, interviews, questionnaires, and system testing in the Lake Toba tourism area. The results demonstrate that the AR-based features effectively improve users’ understanding and awareness of cleanliness issues, while the ML-based system shows strong potential for objective and efficient cleanliness monitoring. Overall, this study highlights the feasibility of AR and ML as complementary technologies to support sustainable and competitive clean tourism management.
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[26] S. Essahraui et al., “Real-Time Driver Drowsiness Detection Using Facial Analysis and Machine Learning Techniques,” Sensors, vol. 25, no. 3, pp. 1–22, 2025, doi: 10.3390/s25030812.
Published
2025-12-16
How to Cite
SIREGAR, Victor Marudut Mulia; MANALU, Andi Setiadi; SARAGIH, Roy Sahputra.
PEMANFAATAN AUGMENTED REALITY DAN MACHINE LEARNING UNTUK EDUKASI DAN PEMANTAUAN KEBERSIHAN DESTINASI WISATA.
Jurnal Teknik Informasi dan Komputer (Tekinkom), [S.l.], v. 8, n. 2, p. 493-502, dec. 2025.
ISSN 2621-3079.
Available at: <https://jurnal.murnisadar.ac.id/index.php?journal=Tekinkom&page=article&op=view&path%5B%5D=2135>. Date accessed: 21 apr. 2026.
doi: https://doi.org/10.37600/tekinkom.v8i2.2135.
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