Penerapan Algoritma Multiclass Ensemble Support Vector Machine dengan Fungsi Kernel untuk Klasifikasi Human Activity
نویسندگان
چکیده
Human Activity Recognition adalah teknologi yang memperkenalkan gerakan tubuh manusia menggunakan accelerometer, giroskop, global positioning system, dan kamera. Awal munculnya metode support vector machine digunakan untuk mengklasifikasi 2 kelas, sehingga diperlukan pengembangan mengatasi permasalahan multikelas banyaknya dataset berskala besar mengakibatkan kinerja menjadi tidak optimal. Tujuan kertas ini menerapkan ensemble Support Vector Machine dalam mengklasifikasikan berjalan, berlari, naik tangga berdasarkan sensor accelerometer gyroscope pada smartphone. Serta melihat ketika kernel linear RBF. Hasil akurasi sebesar 79.66% mengalami peningkatan 88.01% setelah ensemble. Sedangkan RBF 79.51 88.04%
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ژورنال
عنوان ژورنال: Jurnal informatika terpadu
سال: 2022
ISSN: ['2460-8998']
DOI: https://doi.org/10.54914/jit.v8i2.579