<![CDATA[Koperasi Karya Tani Mandiri merupakan koperasi pertanian di Kabupaten Cianjur, Jawa Barat, yang mendistribusikan sayuran segar kepada lima gerai ritel AEON di wilayah Jabodetabek. Permasalahan utama adalah keterlambatan pengiriman akibat keterbatasan armada transportasi (satu truk pendingin), pengelolaan rute yang belum optimal, serta kurangnya sumber daya manusia di gudang. Penelitian ini bertujuan memodelkan proses distribusi dan mengoptimalkan waktu pengiriman menggunakan software AnyLogic dengan pendekatan Sistem Dinamis melalui Causal Loop Diagram (CLD) dan Stock Flow Diagram (SFD). Tiga skenario perbaikan dirumuskan dan diuji melalui analisis sensitivitas terhadap empat parameter kunci: waktu harus sampai di retail, jumlah kendaraan, waktu harus tiba gudang, dan kapasitas gudang. Hasil simulasi menunjukkan bahwa Skenario 1 (penambahan armada menjadi dua unit disertai pembagian rute ke dua zona terdekat) dan Skenario 2 (percepatan keberangkatan supplier pukul 05.00 dengan tiba gudang pukul 08.00) merupakan skenario paling efektif mengeliminasi keterlambatan pengiriman. Skenario 3 (penambahan gudang pendingin dengan pengiriman supplier dua hari sekali) efektif menjaga kesegaran produk namun memerlukan investasi lebih besar. Penelitian ini memberikan rekomendasi praktis bagi manajemen koperasi untuk meningkatkan ketepatan waktu pengiriman dan menjaga kualitas produk sayuran. Kata Kunci: Sistem Dinamis; AnyLogic; Causal Loop Diagram; Distribusi Sayuran; Optimasi Waktu Pengiriman Abstract Koperasi Karya Tani Mandiri is an agricultural cooperative in Cianjur Regency, West Java, distributing fresh vegetables to five AEON retail outlets across the Greater Jakarta area. The main challenge is delivery delays caused by limited transportation fleet (one refrigerated truck), suboptimal route management, and insufficient warehouse workforce. This study aims to model the distribution process and optimize delivery time using AnyLogic software with a System Dynamics approach through Causal Loop Diagrams (CLD) and Stock Flow Diagrams (SFD). Three improvement scenarios were formulated and tested via sensitivity analysis of four key parameters: required arrival time at retail, number of vehicles, required warehouse arrival time, and warehouse capacity. Simulation results indicate that Scenario 1 (adding a second truck with route division into two nearest geographic zones) and Scenario 2 (accelerating supplier departure to 05:00 with warehouse arrival by 08:00, providing a three-hour buffer) are the most effective scenarios for eliminating delivery delays. Scenario 3 (adding cold storage with supplier delivery every two days) effectively maintains product freshness but requires greater capital investment. This study provides practical recommendations for cooperative management to improve delivery punctuality and maintain vegetable product quality. Keywords: System Dynamics; AnyLogic; Causal Loop Diagram; Vegetable Distribution; Delivery Time Optimization]]>
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