ANALISA PERBANDINGAN PERAMALAN DATA PENUMPANG PT KAI ANTARA METODE SIMULASI MONTE CARLO DAN DOUBLE MOVING AVERAGE

  • Bella Budiani Universitas Widyatama
  • Intan Bunga Universitas Widyatama
  • Siti Amalia Universitas Widyatama
  • Faris Gumelar Universitas Widyatama
Keywords: Monte Carlo Simulation, Forecasting, Double Moving Average (DMA)

Abstract

Monte Carlo simulation is used as a method for analyzing a sistem where there is uncertainty. This research was conducted to compare Monte Carlo simulations with the Double Moving Average (DMA) Method of forecasting which gives the final result close to the actual final result. Monte Carlo simulations are based on experiments on probability or probabilistic elements using acak sampling. Data collection on the number of train passengers at PT KAI is done by taking data from the Central Statistics Agency as many as 156 backward periods starting from 2006 to 2018. Data processing is done by means of Monte Carlo simulations and forecasting the Double Moving Average method using Ms. application. Excel to predict the next 12 periods or forecasting for 2019 which is then compared with the original data in the current BPS. Prediction results for the number of passengers in 2019 resulting from Monte Carlo simulations and DMA forecasting shows that the results of forecasting using DMA are closer to the results of BPS data. Prediction results for 2020 from forecasting using DMA shows that there will be a surge in passengers in 2020 of 27.16%.

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Published
2020-08-13
Section
Articles