PENERAPAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) PADA PERAMALAN JUMLAH PENUMPANG BIS RUTE KUNINGAN-PALEMBANG

TRIYANI, REISKA AGIS and Sukanda, Dian Cahyawati and Dwipurwani, Oki (2022) PENERAPAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) PADA PERAMALAN JUMLAH PENUMPANG BIS RUTE KUNINGAN-PALEMBANG. Undergraduate thesis, Sriwijaya University.

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Abstract

The purpose of this study is to estimate the parameters of the forecasting model for the number of passengers on the Kuningan-Palembang bus route and produce a forecast for the 2022 period. The method used is the Seasonal Autoregressive Integrated Moving Average (SARIMA). The data used is the monthly number of bus passengers from January 2015 to December 2021 which consists of in sample and out sample data. In sample data is used to generate model parameters, while out sample data is used for comparison and model evaluation of model parameters. The results of this study indicate that the best model for forecasting the number of bus passengers is the SARIMA model (2,1,3) (0,1,0)^12. The model contains parameters is μ=-0,00019,〖 ϕ〗_1=1,1488,〖 ϕ〗_2=-0,9412,θ_1=1,7778 ,θ_2=-1,7594,θ_3=0,772 and the mathematical equation is 〖 Z〗_t=Z_(t-12)+Z_(t-1)-Z_(t-13)-0,9412〖 Z〗_(t-1)+0,9412 Z_(t-13)+0,9412 Z_(t-2)-0,9412 Z_(t-14)+e_t-1,7778 e_(t-1). Based on obtained model produces an error as measured by the Mean Absolute Percentage Error (MAPE) of 2.5%, meaning that the model has good predictive ability for forecasting the number of bus passengers. The highest number of passengers for the 2020 prediction results, namely in October to November for each 209 to 214 passengers.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Jumlah Penumpang, Peramalan, Deret Waktu, SARIMA
Subjects:	Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Reiska Agis Triyani
Date Deposited:	05 Sep 2022 06:52
Last Modified:	05 Sep 2022 06:52
URI:	http://repository.unsri.ac.id/id/eprint/78331

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