Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm
Journal Title: Mechatronics and Intelligent Transportation Systems - Year 2023, Vol 2, Issue 2
Abstract
This study aims to assess the safety level of the Automatic Dependent Surveillance-Broadcast (ADS-B) signal quality during airplane departures at Sultan Mahmud Badaruddin II Airport. The Aero-track application was utilized to monitor commercial aircraft departures and collect observation data. The collected data underwent processing using data analysis algorithms and labeling processes, resulting in a comprehensive dataset for evaluating ADS-B signal quality. Signal quality was categorized into four levels, and a model was built using the Random Forest algorithm, achieving an accuracy of 99%. Comparative analysis with SVM and Naive Bayes algorithms showed accuracy values of 93% and 97% respectively. Consequently, the Random Forest Model was chosen for estimating ADS-B signal quality during commercial aircraft takeoff and landing.
Authors and Affiliations
Rani Silvani Yousnaidi, Rossi Passarella, Rizki Kurniati, Osvari Arsalan, Aditya, Indra Gifari Afriansyah, Muhammad Rifqi Fathan, Marsella Vindriani
Keywords
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- EP ID EP732236
- DOI https://doi.org/10.56578/mits020202
- Views 34
- Downloads 0
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