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Gulo, Pikir Claudia Septiani
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Prediksi Indeks Harga Saham Gabungan (IHSG) Menggunakan Algoritma Autoregressive Integrated Moving Average (ARIMA) Khaira, Ulfa; Utomo, Pradita Eko Prasetyo; Suratno, Tri; Gulo, Pikir Claudia Septiani
JUSS (Jurnal Sains dan Sistem Informasi) Vol. 2 No. 2 (2019): Jurnal Sains dan Sistem Informasi
Publisher : Prodi Sistem Informasi FST Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/juss.v2i2.8449

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.
Co-Authors Khaira, Ulfa Tri Suratno Utomo, Pradita Eko Prasetyo