PENERAPAN METODE DESEASONALIZED PADA PERAMALAN BANYAK PENUMPANG KERETA API DI PULAU JAWA - Guntur Prabowo; Supriyono Supriyono; Muhammad Kharis (Universitas Muhammadiyah Semarang, 2017)
Forecasting is an estimates of some phenomenon that will be occurredfuture time. Forecasting uses past data that will be analyzed scientifically.Deseasonalized is a part of decomposition methods that be included totime series methods. The base concept of this methods is clear all effects ofseasonal movement or variation, that possibly make us focus on long termmovement. The aim of this research is knowing the form of deseasonalizedmodels and forecasting result of how much the train passenger in JavaIsland at year 2017 and 2018. This forecasting done by counting seasonalindex using ratio methods of moving average, and then determine theequation of the trends. The forecasting calculated by multiplying Y(estimated value) and seasonal index. From this research, we get the deseasonalized model Y=40165,28+2589,163t. The forecasting resultof the number of train passenger in Java Island for first quarters at 2017until forth quarters at 2018 in consecutive series are 90700, 97001,101548, 103688, 100636, 107344, 112095, 114185.