Bandingkan metode

	Simulasi Kejadian Diskrit Skenario Kebijakan	Simulasi Kejadian Diskrit (DES)
Bidang	Simulasi	Simulasi
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	1960s–1990s	1960s (formalized); modern computational form from 1970s onward
Pencetus	Tocher, K. D. and Gordon, G. (early DES); policy scenario extension emerged through operations research and health policy modeling communities	Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
Tipe	Simulation-based policy evaluation	Stochastic process simulation
Sumber perintis	Law, A. M. (2015). Simulation Modeling and Analysis (5th ed.). McGraw-Hill Education. ISBN: 9780073401324	Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127
Alias	Policy DES, Scenario-based DES, Policy simulation DES, DES policy analysis	DES, event-driven simulation, Ayrık Olay Simülasyonu (DES)
Terkait	5	4
Ringkasan	Policy Scenario Discrete-Event Simulation combines the event-by-event fidelity of Discrete-Event Simulation with systematic policy scenario analysis to evaluate how different interventions, regulations, or resource allocations change system performance. By running multiple well-defined policy scenarios through the same DES model, analysts can compare outcomes — throughput, waiting times, costs — across alternatives before real-world implementation.	Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time.