Abstract
Customers can be certain that the fees they are charged are proportional to the amount of running water used or spent by clean water consumers in some households as a result of the usage of a water meter. Neglected water meters can cause losses for both consumers and PDAM companies. The project’s goal was to analyze a water meter using artificial intelligence. While the purpose of the research is to discover the most prevalent causes of water meter degradation, the output of the research is to identify the most destructive variables. This study’s data came from observations and interviews with the Regional Water Company (PDAM) Tirtauli in Pematangsiantar. The Analytical Hierarchy Process (AHP) technique is used to create a decision support system. The following meter damage explanations have been discovered based on information acquired through interviews and fieldwork: Congestion Water Meter (KM-1), Escape Water Meter (KM-2), Deaf Water Meter (KM-3), Gedek Water Meter (KM-4), and Water Meter Broken (KM-5). The Gedek Water Meter (KM-4) has the greatest priority for water meter damage, according to the AHP approach, with a computed value of 0.3211. The study’s findings are expected to increase water meter degradation in the PDAM, perhaps leading to higher customer water bills.
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