ANALISIS PREDIKSI HARGA SAHAM DENGAN MODEL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) PADA JAKARTA ISLAMIC INDEX (JII) - agustin, isnaini nuzula (REKAMAN (Jurnal Riset Ekonomi Bidang Akuntansi dan Manajemen), 2018)
Stock Price prediction is an important aspect for investor in order to maximize stock return. There are two kinds of stock analysis have been develops over the years, fundamental and technical analysis. Technical analysis believes that stock price formed by the trend of its previous price itself. One of modelling technique in technical analysis that widely used by investor is Autoregressive Integrated Moving Average (ARIMA). This paper presents extensive process of building stock price predictive model using the ARIMA model. Jakarta Islamic Index (JII) were evaluated andÂ  predicted the trend of upcoming trading days stock market fluctuations. The research use data of daily closing price during January 2016 to September 2018. The result shows that data stationer in first differencing, thus we use 1 as orde for d. From next results, it can be observed that ARIMA (2,1,2) fit the data with all variables significantly influenced toward upcoming stock price. Coefficient determination and Root Mean Square Erorr have been used for goodness of fit criteria. The model resulted having influence R-square value is 97.2% and Root Mean Square Error 7.524. The ARIMA model then can be used to predict stock price in the next fifteen days.