Silvia Netsyah
Badan Pusat Statistik, Padang, Indonesia

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Peramalan dan deteksi outlier saham perusahaan angkutan laut umum di masa covid-19 dengan pemodelan arima Ilham Thaib; Gesit Thabrani; Silvia Netsyah
Jurnal Kajian Manajemen dan Wirausaha Vol 3, No 1 (2021): Jurnal Kajian Manajemen dan Wirausaha
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jkmw02114850

Abstract

The public sea freight sector is one of the affected by COVID-19. PT. Samudera Indonesia Tbk is one of the sea transportations companies in Indonesia. The ARIMA model in the previous study provided a statistical test with the aim of evaluating the suitability of the model with a p value of less than 0.05 to determine ARIMA by guessing through ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) through stationary data. Outlier detection can be done by plotting the residuals from the specified model. Forecasting data for the next 5 days using the ARIMA (3,1,2) model can be seen that the results of forecasting stock price data for PT. Samudera Indonesia Tbk using ARIMA (3,1,2) is within the 95% confidence interval with a forecast value that is close to the actual value. There are outliers that are detected which are related to economic phenomena.