Open AccessANALISA PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN METODE ARIMA
Author(s) -
Julkifli Purnama,
Ahmad Juliana
Publication year - 2020
Publication title -
cakrawala management business journal
Language(s) - English
Resource type - Journals
eISSN - 2623-0887
pISSN - 2622-9951
DOI - 10.30862/cm-bj.v2i2.51
Subject(s) - autoregressive integrated moving average , akaike information criterion , econometrics , closing (real estate) , time series , statistics , economics , computer science , finance , mathematics
Investment in the capital market every manager needs to analyze to make decisions so that the right target to produce profits in accordance with what is expected. For that, we need a way to predict the decisions that will be taken in the future. The research objective is to find the best model and forecasting of the composite stock price index (CSPI).
Data analysis technique The ARIMA Model time series data from historical data is the basis for forecasting. Secondary data is the closing price of the JCI on July 16 2018 to July 16 2019 to see how accurate the forecasting is done on the actual data at that time.
The results of the study that the best Arima model is Arima 2.1.2 with an R-squared value of 0.014500, Schwarz criterion 10.83497 and Akaike info criterion of 10.77973. Results of forecasting actual data are 6394,609, dynamic forecast 6387,551 selisish -7,05799, statistics forecas 6400,653 difference of 6,043909. For investors or the public can use the ARIMA method to be able to predict or predict the capital market that will occur in the next period.