<![CDATA[The increasing volume of municipal solid waste in Sumenep Regency has created significant challenges for local authorities in selecting an effective and sustainable waste treatment method. The selection process requires consideration of multiple criteria, including economic, technical, environmental, social, labor, and material recovery aspects. Therefore, this study aims to determine the most suitable waste processing method by applying the Analytical Hierarchy Process (AHP) as the primary decision-making approach and an AI-assisted validation approach as a comparative evaluation tool. The AHP method was used to calculate the relative importance of criteria and rank three waste treatment alternatives, namely Composting, Sanitary Landfill, and Incineration, based on expert judgments. To strengthen the reliability of the decision-making process, an AI-assisted evaluation using a Large Language Model (LLM) was conducted to assess the same alternatives according to the established criteria and compare the resulting rankings with those obtained from AHP. The results of the AHP analysis indicate that Composting has the highest priority weight of 48.0%, followed by Sanitary Landfill with 33.5% and Incineration with 18.5%. Similarly, the AI-assisted evaluation generated the highest score for Composting (0.9835), followed by Sanitary Landfill (0.6130) and Incineration (0.6025). The consistency between the rankings produced by AHP and the AI-assisted assessment demonstrates the robustness of the selected alternative. The findings suggest that Composting is the most appropriate waste treatment method for Sumenep Regency due to its superior environmental performance, social acceptance, and material recovery potential. Furthermore, the study highlights the potential of AI-assisted evaluation as a supporting validation tool for enhancing multi-criteria decision-making in waste management planning.]]>
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