Fajriyansah, Muhammad Arif (2023) Klasifikasi Status Erupsi Gunung Berapi Dengan Menggunakan Metode Autocorrelation dan Support Vector Machine. (Classification Of Volcano Eruption Status Using Autocorrelation Method and Support Vector Machine). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.
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Abstract
Volcanic eruption disasters often occur in Indonesia every year, this is because the number of volcanoes in Indonesia is currently still active. Monitoring from the mountain is still far from ideal, both in terms of equipment and human resources (HR). Classification of volcanic eruption status is one of the applications of technology that will be very useful for local residents and the government to minimize losses both victims and material. With that, a combination of the Support Vector Machine method was carried out for classifying the status of volcanic eruptions and the Autocorrelation method for detecting earthquake events in seismic signal data. The z-score method is used to normalize the data. This study also compares the performance of SVM kernels, namely linear, polynomial, and RBF where the polynomial kernel with parameter degree = 2 has the best performance in the case of seismic signal classification with an accuracy of 0.9605 at a data ratio of 90:10. Furthermore, the Z-Score contributes positively to a significant increase in the accuracy of the SVM model in the case of seismic signal classification. Keywords: Autocorrelation, Classification, Support Vector Machine, Volcano
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Autocorrelation, Classification, Support Vector Machine, Volcano |
Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Teknik > Program Studi Teknik Informatika |
Depositing User: | 1461900226 Muhammad Arif Fajriyansah |
Date Deposited: | 08 Dec 2023 02:35 |
Last Modified: | 08 Dec 2023 02:35 |
URI: | http://repository.untag-sby.ac.id/id/eprint/27920 |
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