Article Per Year (5 Year)
p-Index From 2021 - 2026
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All Journal Infolitika Journal of Data Science
Muslim Amiren
Department of Informatics, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Internet Bandwidth Forecasting by Using Fuzzy Time Series in Zainal Abidin General Hospital, Indonesia Khalid Rianda; Muhd Iqbal; Muslim Amiren; Maulyanda Maulyanda; Afdhaluzzikri Afdhaluzzikri; Intan Syahrini; Siti Rusdiana; Abdul Fikri; Irvanizam Irvanizam
Infolitika Journal of Data Science Vol. 4 No. 1 (2026): May 2026
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v4i1.428

Abstract

Data bandwidth capacity is a critical component of internet infrastructure management, directly impacting network efficiency and operational costs. Accurate measurement and forecasting of bandwidth requirements are essential to optimize resource allocation. This study utilizes a Fuzzy Time Series (FTS) approach for bandwidth forecasting, leveraging its ability to capture complex patterns from historical data without requiring the rigid statistical assumptions of classical forecasting methods. A forecasting model was developed and implemented to predict data bandwidth requirements at the Zainal Abidin General Hospital (RSUZA). Utilizing historical data collected from February 1, 2019, to April 29, 2019, the model's performance was evaluated using the Mean Absolute Percentage Error (MAPE). The proposed method achieved a MAPE of 6.45%, demonstrating high accuracy and falling into the "highly accurate" category.
Co-Authors Abdul Fikri Afdhaluzzikri Afdhaluzzikri Intan Syahrini Irvanizam Zamanhuri Khalid Rianda Maulyanda, Maulyanda Muhd Iqbal Siti Rusdiana