YOUSNAIDI, RANI SILVANI and Passarella, Rossi and Kurniati, Rizki (2023) KLASIFIKASI KUALITAS SINYAL ADS-B PADA DATA KEBERANGKATAN PENERBANGAN DI BANDARA SULTAN MAHMUD BADARUDDIN II MENGGUNAKAN PENDEKATAN MACHINE LEARNING. Undergraduate thesis, Sriwijaya University.
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Abstract
The high risk of aircraft accidents, 63% during takeoff and 49% during the landing process, can be analyzed through ADS-B signal data owned by flights. The data collected through the AERO-TRACK application is processed with the aim of knowing the quality of ADS-B signals at Sultan Mahmud Badaruddin II Airport and the method that has the best performance in classifying imbalanced data into 4 different class labels. The results showed that the ADS-B signal quality was good because the majority of the data, namely 1.328 data, was labeled as Tier 1 with the f1-score performance of each classification method, namely 91% for Random Forest, 68% using the Naïve Bayes algorithm and 28% for the SVM algorithm.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | ADS-B, Signal Quality, Classification, SVM, Random Forest, Naïve Bayes |
Subjects: | T Technology > T Technology (General) > T1-995 Technology (General) > T14 Philosophy. Theory. Classification. Methodology Cf. CB478 Technology and civilization |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | Rani Silvani Yousnaidi |
Date Deposited: | 26 Jun 2023 02:19 |
Last Modified: | 26 Jun 2023 02:19 |
URI: | http://repository.unsri.ac.id/id/eprint/113208 |
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