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Learning Outcomes

Learning Outcomes. Mahasiswa akan dapat menjelaskan definisi, pengertian, klasifikasi, motivasi penggunaan simulasi,model simulasi dan langkah-langkah proses simulasi. Outline Materi:. Pengertian simulasi Klasifikasi model simulasi Motivasi menggunakan simulasi

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Learning Outcomes

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  1. Learning Outcomes • Mahasiswa akan dapat menjelaskan definisi, pengertian, klasifikasi, motivasi penggunaan simulasi,model simulasi dan langkah-langkah proses simulasi.

  2. Outline Materi: • Pengertian simulasi • Klasifikasi model simulasi • Motivasi menggunakan simulasi • Langkah-langkah proses simulasi

  3. Pengertian Simulasi (Simulation) Simulation: a descriptive technique that enables a decision maker to evaluate the behavior of a model under various conditions. • Simulation models complex situations • Models are simple to use and understand • Models can play “what if” experiments • Extensive software packages available

  4. Simulation Process • Identify the problem • Develop the simulation model • Test the model • Develop the experiments • Run the simulation and evaluate results • Repeat 4 and 5 until results are satisfactory

  5. Monte Carlo Simulation Monte Carlo method: Probabilistic simulation technique used when a process has a random component • Identify a probability distribution • Setup intervals of random numbers to match probability distribution • Obtain the random numbers • Interpret the results

  6. Simulated value Random number Standard deviation = + X Mean Simulating Distributions • Poisson • Mean of distribution is required • Normal • Need to know the mean and standard deviation

  7. Simulated value = a + (b - a)(Random number as a percentage) Uniform Distribution F(x) 0 a b x

  8. F(t) 0 T t Negative Exponential Distribution

  9. Computer Simulation • Simulation languages • SIMSCRIPT II.5 • GPSS/H • GPSS/PC • RESQ

  10. Advantages of Simulation • Solves problems that are difficult or impossible to solve mathematically • Allows experimentation without risk to actual system • Compresses time to show long-term effects • Serves as training tool for decision makers

  11. Limitations of Simulation • Does not produce optimum solution • Model development may be difficult • Computer run time may be substantial • Monte Carlo simulation only applicable to random systems

  12. Terima kasih Semoga Berhasil

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