Aulia Fahreza Ismanto
Department of Electrical Engineering, Faculty of Engineering, Universitas Muhammadiyah Jakarta, 10510 Jakarta, Indonesia

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Behavioral Determinants of Environmental Health Impacts in IoT-Enabled Waste Management: Evidence from Greater Jakarta Urban Households E. Ernyasih; N. Nelfiyanti; Eka Samsul Ma’arif; Aulia Fahreza Ismanto; Donita Lutfia Hasanah; D. Daruki
Journal of Public Health and Pharmacy Vol. 6 No. 2 (2026)
Publisher : Pusat Pengembangan Teknologi Informasi dan Jurnal Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jphp.v6i2.8682

Abstract

Introduction: The rapid growth of household waste in urban areas poses a serious challenge to environmental health. The integration of the IoT into waste management is considered an innovative solution, offering real-time monitoring, collection efficiency, and greater system transparency. This study aims to examine the influence of perception, attitude, awareness, and practices on environmental health impacts in the context of IoT adoption. Methods: A cross-sectional survey was conducted with 120 households in the Greater Jakarta area, and the data were analyzed using SEM-PLS. Results: The results reveal that perception significantly influences attitude (p < 0.001), and attitude significantly influences awareness (p < 0.001). The structural model demonstrates strong predictive power with R² values of 0.566 for attitude, 0.552 for awareness, and 0.839 for environmental health impacts. Standardized path coefficients show significant effects for perception ? attitude (? = 0.752; p < 0.001), attitude ? awareness (? = 0.743; p < 0.001), and practices ? environmental health impact (? = 0.864; p < 0.001). Model diagnostics confirm reliability and validity, including AVE > 0.50, CR > 0.70, HTMT < 0.85, and VIF < 3. However, awareness does not directly affect environmental health (p > 0.05), indicating the presence of an intention–behavior gap. In contrast, actual waste management practices emerged as the most dominant predictor, with the largest effect on environmental health outcomes (p < 0.001). Conclusion: These findings highlight the necessity of policy strategies that go beyond raising awareness and digital literacy, ensuring the transformation of awareness into consistent practices through adequate infrastructure, incentive systems, and regulatory enforcement. This study contributes to strengthening the concept of smart cities and supports sustainable development strategies in urban settings.