Prediksi Indeks Bursa Efek Indonesia 2023 Pendekatan ARIMA, Machine Learning dengan R Programming - R. A. E. Virgana Targa Sapanji; Sri Lestari; Murnawan Murnawan; Rosalin Samiharjo (Jurnal Manajemen Informatika JAMIKA, 2023)
The Indonesian Stock Exchange Index (BEI) is the main indicator of the Indonesian stock market. The problem in this research is a specific issue to solve the practical problem of predicting the future movement of the BEI index which has strategic value for investors, traders and companies in Indonesia. The aim of this research is to be able to predict the BEI index until the end of 2023, because the stock exchange plays a big role for the Indonesian economy as an economic and financial function. Traditional approaches such as ARIMA (Autoregressive Integrated Moving Average) have been used to predict the movement of the BEI index. However, in recent years, machine learning and data mining techniques have become popular as more sophisticated alternative approaches. This research uses a combined approach between ARIMA and machine learning with R Programming. Daily IDX index data from January 2012 to December 2022 will be taken from Yahoo Finance. This data will then be cleaned and processed using R Programming. The ARIMA approach will be used as a baseline to compare machine learning performance. The results focus on the estimated closing stock prices for the next 365 days or the average until the end of 2023. The Time Series value of the possible minimum/maximum predicted value for IDX shares in 2023 is a minimum predicted value of 6786,212 - 6849,559, a maximum predicted value of 6850,093 - 7086,012. Trends represent a good approach in predicting the future direction of closing prices.