Modeling The Prediction of Hard Drive Capacity Usage on Server Computers Based on Linear Regression

Wahyuni Wahyuni; Pitrasacha Adytia; Siti Namira Rizqi Astin; Kelik Sussolaikah

doi:10.24014/ijaidm.v7i1.28851

Modeling The Prediction of Hard Drive Capacity Usage on Server Computers Based on Linear Regression

Wahyuni Wahyuni, Pitrasacha Adytia, Siti Namira Rizqi Astin, Kelik Sussolaikah

Abstract

Bank of XYZ has a server computer that is used to run several information technology application services such as ATMs and others. Because the server computer uses a hard drive, the full hard drive can cause problems with the service not operating properly. Full hard drives occur without being noticed. So that this makes the computer server problematic, resulting in customer dissatisfaction and decreased customer loyalty to Bank XYZ. To solve the problem at XYZ Bank, one of the machine learning algorithms can be used to predict hard drive capacity. The method used to predict hard drive storage or usage. The machine learning algorithm used is Multiple Linear Regression. The results of this study show that the linear regression model successfully predicts the use of hard drive capacity on server computers with a sufficient level of accuracy.But it is still not optimal because only a few servers can be predicted. For further research, may consider using the LSTM (Long Short-Term Memory) algorithm. LSTM is an algorithm that is well-suited for sequence prediction problems, including time series forecasting.

Keywords

CRISP-DM; Hard Drive Capacity; Linear Regression; Machine Learning; Prediction

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DOI: http://dx.doi.org/10.24014/ijaidm.v7i1.28851

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