Prediksi Indeks Harga Saham Gabungan (IHSG) Menggunakan Algoritma Autoregressive Integrated Moving Average (ARIMA)

  • Ulfa Khaira Universitas Jambi
  • Pradita Eko Prasetyo Utomo Universitas Jambi
  • Tri Suratno Universitas Jambi
  • Pikir Claudia Septiani Gulo Universitas Jambi
Keywords: IHSG, Forecasting, ARIMA

Abstract

There are various types of investment in Indonesia, one of which is the Indeks Harga Saham Gabungan (IHSG) or in English it is called the Indonesia Composite Index, ICI, or IDX Composite. IHSG is an important parameter to consider when making an investment considering that IHSG is a joint stock. This study aims to predict the price of the IHSG with data mining techniques using an algorithm that can be used as a reference for investors when making an investment. ARIMA is a model for generating estimates from historical data. Data in this study were collected from the monthly IHSG from January 4, 2010 - November 26, 2019. Based on the correlation plot, two autocorrelations (lag 1, lag 32) were found to be significant. This model can predict with an average percentage error of 0.004 so that this prediction is considered good enough to predict the stock price of the IHSG.

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Published
2019-12-30
How to Cite
Khaira, U., Utomo, P. E. P., Suratno, T., & Gulo, P. C. S. (2019). Prediksi Indeks Harga Saham Gabungan (IHSG) Menggunakan Algoritma Autoregressive Integrated Moving Average (ARIMA). JUSS (Jurnal Sains Dan Sistem Informasi), 2(2), 11-17. Retrieved from https://online-journal.unja.ac.id/JUSS/article/view/8449