MODELING THE IDX30 STOCK INDEX USING STEP FUNCTION INTERVENTION ANALYSIS

The significant decline in the IDX30 stock index occurred due to an intervention, namely the COVID-19 pandemic, which affected market stability and investment decisions. This study aims to model and forecast the IDX30 stock index using intervention analysis with a step function, which is very suitable for capturing long-term external shocks. The methodology used includes the ARIMA (AutoRegressive Integrated Moving Average) model combined with step function intervention analysis to account for structural changes due to external disturbances. The data used is sourced from investing.com, consisting of weekly IDX30 stock index prices from January 2019 to December 2023. The results show that the COVID-19 pandemic significantly impacted the IDX30 index, causing a drastic decline. The best model identified is ARIMA (1,2,1) with intervention parameters b = 0, s = 0, and r = 1. The forecasting results range from Rp. 488 to Rp. 505, with a Mean Absolute Percentage Error (MAPE) of 1.9404%, which shows the forecasting results are very good, indicating high forecasting accuracy. These findings highlight the effectiveness of intervention analysis in modeling financial time series data affected by external disturbances.

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Journal
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Published
2025-07-01
DOI
https://doi.org/10.30598/barekengvol19iss3pp2057-2068
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

MODELING THE IDX30 STOCK INDEX USING STEP FUNCTION INTERVENTION ANALYSIS

Hartayuni Sain, Fadjryani Fadjryani, Rais Rais, Iman Setiawan et al.
BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN
Complex Systems and Time Series Analysis
article

MODELING THE IDX30 STOCK INDEX USING STEP FUNCTION INTERVENTION ANALYSIS

Hartayuni Sain, Fadjryani Fadjryani, Rais Rais, Iman Setiawan, Junaidi Junaidi, Dini Aprilia Afriza
article en

Abstract

The significant decline in the IDX30 stock index occurred due to an intervention, namely the COVID-19 pandemic, which affected market stability and investment decisions. This study aims to model and forecast the IDX30 stock index using intervention analysis with a step function, which is very suitable for capturing long-term external shocks. The methodology used includes the ARIMA (AutoRegressive Integrated Moving Average) model combined with step function intervention analysis to account for structural changes due to external disturbances. The data used is sourced from investing.com, consisting of weekly IDX30 stock index prices from January 2019 to December 2023. The results show that the COVID-19 pandemic significantly impacted the IDX30 index, causing a drastic decline. The best model identified is ARIMA (1,2,1) with intervention parameters b = 0, s = 0, and r = 1. The forecasting results range from Rp. 488 to Rp. 505, with a Mean Absolute Percentage Error (MAPE) of 1.9404%, which shows the forecasting results are very good, indicating high forecasting accuracy. These findings highlight the effectiveness of intervention analysis in modeling financial time series data affected by external disturbances.

BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPANVol. 19(3)
Tadulako University (ID)
Universitas Tadulako
Openalex Percentile: Top 77%
Complex Systems and Time Series Analysis
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MODELING THE IDX30 STOCK INDEX USING STEP FUNCTION INTERVENTION ANALYSIS — Hartayuni Sain, Fadjryani Fadjryani, et al. · BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN (2025) | TGRS Research Map | TGRS