Analisis Pengembangan Startup SmartWaste AI Berbasis Internet of Things dan Artificial Intelligence Menggunakan Pendekatan Mixed Methods untuk Mendukung Smart City Berkelanjutan
DOI:
https://doi.org/10.47065/jieee.v5i4.3313Keywords:
Artificial Intelligence; Internet of Things; Smart City; SmartWaste AI; Waste ManagementAbstract
Population growth, urbanization, and economic activities have continuously increased the volume of municipal solid waste each year, while conventional waste management systems have not been able to cope with these growing challenges. Waste bin capacity monitoring is still largely conducted manually, resulting in delays in waste collection, waste accumulation, inefficient fleet utilization, and limited use of data to support decision-making. In addition, there is no integrated system that combines real-time monitoring, data analytics, and waste volume prediction to enable more effective waste management. This study aims to analyze the current condition of waste management, identify the potential application of the Internet of Things (IoT) and Artificial Intelligence (AI), and examine the development of the SmartWaste AI startup as an intelligent waste management solution to support sustainable Smart City initiatives. The research employed a mixed methods approach using an explanatory-descriptive design. Data were collected through in-depth interviews, observations, and documentation, and subsequently analyzed using the Miles, Huberman, and Saldaña interactive analysis model, complemented by a business feasibility analysis. The results indicate that the waste management system handles approximately 75 tons of waste per month, with major challenges including increasing waste volume, limited monitoring systems, and low community participation in waste segregation. The implementation of IoT has the potential to reduce waste collection delays by up to 50% and prevent approximately three waste accumulation incidents per month, while AI is capable of predicting waste volume with an accuracy exceeding 80%. The integration of these technologies through the SmartWaste AI startup is estimated to improve operational efficiency by 27.5%, reduce waste accumulation, accelerate service delivery, and support the realization of a cleaner, smarter, and more sustainable Smart City. Therefore, SmartWaste AI has the potential to become a strategic innovation in the digital transformation of waste management systems in Indonesia.
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