PERAMALAN HARGA SAHAM PT. BANK RAKYAT INDONESIA (PERSERO) TBK MENGGUNAKAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

The stock price movements are important in the stock market because they provide information about company performance, market sentiment and other economic factors. This makes stock price movements important to monitored by investors, analysts and other market participants to make the right investment decisions when to buy or sell these stocks. The aims of the research is to predict the stock price of PT. Bank Rakyat Indonesia (Persero) Tbk using the Auto Regressive Integrated Moving Average (ARIMA) method. The ARIMA method is used to predict future values based on historical data. The data used is the stock price of PT. Bank Rakyat Indonesia (Persero) Tbk from 3 July 2023 to 28 March 2024 that obtained from the Yahoo Finance website. There are four steps that will be used. First, explore the data to get a general description of the used data. Second, identify data stationarity. Third, identify the ARIMA model that will be used. Fourth, predict the stock price of PT. Bank Rakyat Indonesia (Persero) for April 2024 period. The result is the most optimal model for predicting stoke prices of PT. Bank Rakyat Indonesia (Persero) in the April 2024 period is ARIMA (1,1,1).

Authors

Publication Details

Journal
KadikmA
Published
2025-02-12
DOI
https://doi.org/10.19184/kdma.v15i1.53679
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

PERAMALAN HARGA SAHAM PT. BANK RAKYAT INDONESIA (PERSERO) TBK MENGGUNAKAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

Miftahur Ro'ifah, Fita Fatimah, Dwi Noviani Sulisawati
KadikmA
Management and Optimization Techniques
article

PERAMALAN HARGA SAHAM PT. BANK RAKYAT INDONESIA (PERSERO) TBK MENGGUNAKAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA)

Miftahur Ro'ifah, Fita Fatimah, Dwi Noviani Sulisawati
article en

Abstract

The stock price movements are important in the stock market because they provide information about company performance, market sentiment and other economic factors. This makes stock price movements important to monitored by investors, analysts and other market participants to make the right investment decisions when to buy or sell these stocks. The aims of the research is to predict the stock price of PT. Bank Rakyat Indonesia (Persero) Tbk using the Auto Regressive Integrated Moving Average (ARIMA) method. The ARIMA method is used to predict future values based on historical data. The data used is the stock price of PT. Bank Rakyat Indonesia (Persero) Tbk from 3 July 2023 to 28 March 2024 that obtained from the Yahoo Finance website. There are four steps that will be used. First, explore the data to get a general description of the used data. Second, identify data stationarity. Third, identify the ARIMA model that will be used. Fourth, predict the stock price of PT. Bank Rakyat Indonesia (Persero) for April 2024 period. The result is the most optimal model for predicting stoke prices of PT. Bank Rakyat Indonesia (Persero) in the April 2024 period is ARIMA (1,1,1).

KadikmAVol. 15(1)
Openalex Percentile: Top 70%
Management and Optimization Techniques
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PERAMALAN HARGA SAHAM PT. BANK RAKYAT INDONESIA (PERSERO) TBK MENGGUNAKAN METODE AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) — Miftahur Ro'ifah, Fita Fatimah, et al. · KadikmA (2025) | TGRS Research Map | TGRS