JuSTISe: Journal Data Science, Technology, Informatics and Security
Vol 1 No 1 (2023): Journal Data Science, Technology, Informatics and Security (Juni 2023)

A Scrum-Driven Software Development of IoT-Integrated Smart Trash Solution with UV-C Sterilization and Blackbox Testing

Dian Resti Juliani (Universitas Kebangsaan Republik Indonesia)
Irman Hariman (Universitas Kebangsaan Republik Indonesia)



Article Info

Publish Date
26 Jun 2023

Abstract

Serious challenges in waste management in Indonesia have had a significant impact on health and the environment. The excessive accumulation of waste has led to new issues, including a decline in environmental quality and the spread of diseases. This study employs a qualitative approach to address this problem. The Scrum methodology is employed in software development, with an emphasis on blackbox testing and Boundary Value Analysis (BVA). Research findings reveal issues in waste management, including excessive accumulation and bacterial growth in waste disposal sites. A proposed solution is presented through an IoT and Android-based "Smart Trash" system, incorporating weight and height sensors for waste, UV-C Lamp technology, and notification delivery to Android devices. A prototype of this tool is tested to optimize waste monitoring and management. The research findings conclude that this smart waste disposal system facilitates monitoring and notifications for sanitation workers, while aiding in minimizing bacterial growth in waste. With this system in place, sanitation workers can manage waste transportation more efficiently. However, this tool holds potential for further development, such as bacterial detection in waste.

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Journal Info

Abbrev

justise

Publisher

Subject

Description

JuSTISe: Journal Data Science, Technology, Informatics and Security adalah jurnal ilmiah nasional yang ditinjau oleh sejawat (peer-reviewed) dan diterbitkan oleh Universitas Kebangsaan Republik Indonesia. Jurnal ini berfokus pada publikasi hasil penelitian berkualitas tinggi di bidang ilmu data ...