Skripsi

IMPLEMENTASI MODEL AUTOREGRESSIVE INTGRATED MOVING AVERAGE (ARIMA) DALAM PERAMALAN HARGA CRYPTOCURRENCY JENIS ETHEREUM TAHUN 2025

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Ethereum (ETH) is one of the largest cryptocurrency by market capitalization and is widely utilized in various blockchain-based applications. The fluctuating nature of Ethereum’s price requires forecasting to assist investors in predicting potential price movements and investment risks. This study aims to identify the best ARIMA model for forecasting daily Ethereum prices. The data used consist of daily Ethereum prices from January 1, 2025 to October 31, 2025 obtained from the CoinMarketCap website. The analysis procedures include stationarity testing using the Box-Cox transformation and differencing, model identification through ACF and PACF analysis, parameter estimation using the least squares method, and diagnostic checking using the Ljung-Box test to ensure that the residuals satisfy the White Noise assumption. From several tentative ARIMA, the best model obtained was ARIMA (0,2,1). This model is statistically significant, fulfills the White Noise assumption, and produces a Mean Absolute Percentage Error (MAPE) of 11.8%, which indicates a good level of forecasting accuracy. The ARIMA (0,2,1) model was then used to forecast Ethereum prices for the period of November 1, 2025 to December 31, 2025

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Detail Information

Series Title

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Call Number

T1903092025

Publisher

Indralaya : Prodi Ilmu Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2025

Collation

xviii, 111 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

332.645 07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Prodi Ilmu Matematika
Peramalan Harga Pasar

Specific Detail Info

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Statement of Responsibility

MI

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