Abstract
Cryptocurrencies have received a lot of attention from investors, researchers, regulators, and the media. It is a known fact that the cryptocurrency price is very volatile and has anomaly effects. However, not enough scientific research has been done in the Business Intelligence cryptocurrency calendar anomaly detection area. This study presented the development of Business Intelligence dashboards with real data. As a result of this application, anomaly detection was carried out in the values from the Finance Yahoo API collected data set. With the corresponding BI application, a time-dependent representation of cryptocurrency price can be captured and analyzed, and anomalies can be selected and evaluated. The factors that play a role in forming the model to be applied in detecting anomalies with the experimental results were formed and investigated.
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