<![CDATA[This research proposes the implementation of the Simple Additive Weighting (SAW) method as an approach to determine priorities for school toilet cleanliness based on IoT. The system integrates temperature, humidity, and ammonia gas sensors as key indicators to measure the cleanliness condition of toilets. The SAW method is employed to calculate the relative weight of each parameter, which is then used to assign priority scores. The system operates by utilizing temperature sensors to identify the toilet's environmental temperature, humidity sensors to measure humidity levels, and ammonia gas sensors to detect ammonia concentration, a crucial indicator of toilet cleanliness. Data from these sensors are collected and processed using the SAW method, enabling the automatic determination of toilet cleanliness priorities. The success of this implementation is tested through simulations and field testing. Experimental results demonstrate that the system is capable of providing priority scores with high accuracy, allowing for more efficient management of toilet cleanliness. Other advantages include the system's ability to provide real-time notifications to relevant parties through the IoT platform, facilitating prompt corrective actions. This research contributes to the development of intelligent solutions for school toilet cleanliness management, integrating IoT technology and the SAW method to provide a measurable and effective approach. With the adoption of this system, it is expected to enhance the quality of school toilet sanitation, support student health, and optimize school facility management.]]>
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