PREDIKSI HARGA SAHAM SEKTOR PERBANKAN PADA BADAN USAHA MILIK NEGARA DI BURSA EFEK INDONESIA

Bernas, Aqli (2024) PREDIKSI HARGA SAHAM SEKTOR PERBANKAN PADA BADAN USAHA MILIK NEGARA DI BURSA EFEK INDONESIA. Undergraduate thesis, Universitas Muhammadiyah Malang.

[thumbnail of PENDAHULUAN.pdf]
Preview
Text
PENDAHULUAN.pdf

Download (4MB) | Preview
[thumbnail of BAB I.pdf]
Preview
Text
BAB I.pdf

Download (2MB) | Preview
[thumbnail of BAB II.pdf]
Preview
Text
BAB II.pdf

Download (5MB) | Preview
[thumbnail of BAB III.pdf] Text
BAB III.pdf
Restricted to Registered users only

Download (1MB) | Request a copy
[thumbnail of BAB IV.pdf] Text
BAB IV.pdf
Restricted to Registered users only

Download (3MB) | Request a copy
[thumbnail of BAB V.pdf] Text
BAB V.pdf
Restricted to Registered users only

Download (442kB) | Request a copy
[thumbnail of LAMPIRAN.pdf] Text
LAMPIRAN.pdf
Restricted to Registered users only

Download (8MB) | Request a copy

Abstract

This study predicts the stock prices of the banking sector in BUMN for the period from December 1, 2024, to February 28, 2025, using the Autoregressive Integrated Moving Average (ARIMA) model. The data used consists of historical closing prices of banking sector stocks from September 1, 2024, to November 30, 2024. The research steps include: Data Presentation, Data Plotting, Stationarity Testing, Determination of ARIMA parameters p, d, and q, and Prediction. The prediction results indicate that the stocks of Bank Rakyat Indonesia (BBRI) and Bank Mandiri (BMRI) show a downward trend (bearish), the stocks of Bank Negara Indonesia (BBNI), Bank Tabungan Negara (BBTN), and Bank Raya Indonesia (AGRO) show a sideways price movement, and the stocks of Bank Syariah Indonesia (BRIS) show an upward trend (bullish). Investors are advised to make buy decisions on undervalued stocks and sell decisions on overvalued stocks. This study is expected to enrich the literature in the field of investment with a focus on stock price prediction using the autoregressive integrated moving average (ARIMA) model and to serve as a reference for future research. This study can be used as an educational resource for short-term investors who focus on earning stock income from capital gains.

Item Type: Thesis (Undergraduate)
Student ID: 202110160311020
Keywords: ARIMA, BUMN, Prediction
Subjects: H Social Sciences > HG Finance
Divisions: Faculty of Economics and Business > Department of Management (61201)
Depositing User: 202110160311020 aqlibernas
Date Deposited: 23 Jan 2025 09:57
Last Modified: 23 Jan 2025 09:57
URI: https://eprints.umm.ac.id/id/eprint/14118

Actions (login required)

View Item
View Item