Proyeksi Harga Saham Perbankan BUMN Dengan Metode Trend Analysis

The capital market plays a crucial role in economic growth by serving as a platform for long-term financial instruments, including stocks, bonds, and mutual funds. Stock price movements are influenced by various factors, both internal and external, making accurate forecasting essential for investors to minimize risks and optimize returns. This study aims to forecast the stock prices of state-owned banks (BUMN) in Indonesia using the Trend Analysis method, specifically employing linear, quadratic, exponential growth, and S-curve models. The research utilizes historical closing price data from September 2024 to January 2025, covering four major state-owned banks: Bank Rakyat Indonesia (BBRI), Bank Mandiri (BMRI), Bank Negara Indonesia (BBNI), and Bank Tabungan Negara (BBTN). The analysis is conducted using Minitab software, and the best forecasting model is determined based on the lowest values of Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD). The results indicate that the quadratic model provides the most accurate forecasts for all four banks, capturing non-linear trends in stock price movements. The findings reveal a consistent downward trend in stock prices across all BUMN banks, highlighting potential market pressures and economic conditions that may affect future performance. This suggests that investors should approach short- to medium-term investments with caution. Additionally, while trend analysis offers valuable insights into historical patterns, integrating fundamental and technical analysis is recommended to enhance investment decision-making.

Authors

Publication Details

Journal
Jurnal Ilmiah Raflesia Akuntansi
Published
2025-04-24
DOI
https://doi.org/10.53494/jira.v11i1.833
Primary Topic
Management and Optimization Techniques
Type
article
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article

Proyeksi Harga Saham Perbankan BUMN Dengan Metode Trend Analysis

Fatiya Maliha, Diah Anggeraini Hasri
Jurnal Ilmiah Raflesia Akuntansi
Management and Optimization Techniques
article

Proyeksi Harga Saham Perbankan BUMN Dengan Metode Trend Analysis

Fatiya Maliha, Diah Anggeraini Hasri
article en

Abstract

The capital market plays a crucial role in economic growth by serving as a platform for long-term financial instruments, including stocks, bonds, and mutual funds. Stock price movements are influenced by various factors, both internal and external, making accurate forecasting essential for investors to minimize risks and optimize returns. This study aims to forecast the stock prices of state-owned banks (BUMN) in Indonesia using the Trend Analysis method, specifically employing linear, quadratic, exponential growth, and S-curve models. The research utilizes historical closing price data from September 2024 to January 2025, covering four major state-owned banks: Bank Rakyat Indonesia (BBRI), Bank Mandiri (BMRI), Bank Negara Indonesia (BBNI), and Bank Tabungan Negara (BBTN). The analysis is conducted using Minitab software, and the best forecasting model is determined based on the lowest values of Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD). The results indicate that the quadratic model provides the most accurate forecasts for all four banks, capturing non-linear trends in stock price movements. The findings reveal a consistent downward trend in stock prices across all BUMN banks, highlighting potential market pressures and economic conditions that may affect future performance. This suggests that investors should approach short- to medium-term investments with caution. Additionally, while trend analysis offers valuable insights into historical patterns, integrating fundamental and technical analysis is recommended to enhance investment decision-making.

Jurnal Ilmiah Raflesia AkuntansiVol. 11(1)
Openalex Percentile: Top 88%
Management and Optimization Techniques
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Proyeksi Harga Saham Perbankan BUMN Dengan Metode Trend Analysis — Fatiya Maliha, Diah Anggeraini Hasri · Jurnal Ilmiah Raflesia Akuntansi (2025) | TGRS Research Map | TGRS