Food waste merupakan permasalahan lingkungan yang signifikan di sektor perhotelan akibat tingginya aktivitas produksi dan konsumsi makanan. Pemanfaatan teknologi berbasis Artificial Intelligence (AI) menjadi salah satu upaya untuk mendukung pengelolaan food waste melalui pengukuran yang lebih akurat. Penelitian ini bertujuan untuk menganalisis perbedaan timbulan food waste yang direpresentasikan oleh sampah organik sebelum dan sesudah implementasi teknologi berbasis AI di Hotel X pada periode 2022–2024, serta menggambarkan karakteristik food waste berdasarkan pengukuran teknologi AI pada outlet all-day dining. Penelitian ini menggunakan desain kuantitatif komparatif dengan data sekunder berupa timbulan sampah organik bulanan sebelum (Juli 2022–Juni 2023) dan sesudah (Juli 2023–Juni 2024) implementasi teknologi AI, serta data food waste terukur berbasis AI. Analisis dilakukan secara univariat dan bivariat menggunakan uji Wilcoxon Signed Rank Test. Hasil penelitian menunjukkan bahwa rata-rata timbulan sampah organik sebelum implementasi teknologi AI sebesar 20.081,67 kg/bulan dan setelah implementasi sebesar 20.808,92 kg/bulan, serta tidak terdapat perbedaan yang signifikan secara statistik (p = 0,583). Namun, pengukuran berbasis AI menunjukkan penurunan food waste sebesar 7,7% pada tingkat outlet. Temuan ini menunjukkan bahwa teknologi berbasis AI berperan dalam meningkatkan kualitas pengukuran dan pengelolaan food waste, meskipun belum berdampak signifikan terhadap penurunan timbulan sampah organik secara keseluruhan.

Food waste is a significant environmental problem in the hospitality sector due to high food production and consumption activities. The use of Artificial Intelligence (AI) technology is one of the approaches to provide support for food waste management through more accurate measurement. This study aims to analyze the differences in food waste represented by organic waste before and after the implementation of AI-based technology at Hotel X in the period 2022–2024, as well as to describe the characteristics of food waste based on AI technology measurements at all-day dining outlets. This study uses a comparative quantitative design with secondary data in the form of monthly organic waste generation before (July 2022–June 2023) and after (July 2023–June 2024) the implementation of AI technology, as well as AI-based measured food waste data. The analysis was conducted univariately and bivariately using the Wilcoxon Signed Rank Test. The results showed that the average organic waste generation before the implementation of AI technology was 20,081.67 kg/month and after implementation was 20,808.92 kg/month, with no statistically significant difference (p = 0.583). However, AI-based measurements showed a 7.7% reduction in food waste at the outlet level. These findings indicate that AI-based technology plays a role in improving the quality of food waste measurement and management, although it has not had a significant impact on reducing total organic waste generation.