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All Journal Jurnal Informatika Terpadu
M Rezky Armansyah
Universitas Pancasakti
Computer Science & IT Decision Sciences, Operations Research & Management Education

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Penerapan Algoritma Multiclass Ensemble Support Vector Machine dengan Fungsi Kernel untuk Klasifikasi Human Activity Firman Aziz; Syahrul Usman; Jeffry Jeffry; Nur Ayu Asrhi; M Rezky Armansyah
Jurnal Informatika Terpadu Vol 8 No 2 (2022): September, 2022
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v8i2.579

Abstract

Human Activity Recognition is a technology that introduces human body movement using an accelerometer, gyroscope, global positioning system, and camera. The early emergence of the support vector machine method was used to classify 2 classes, so development was needed to overcome multiclass problems and a large number of large-scale datasets resulted in suboptimal performance. The purpose of this paper is to apply the ensemble Support Vector Machine method in classifying the movement of walking, running, and climbing stairs based on accelerometer and gyroscope sensors on smartphones. And see the performance of the Ensemble Support Vector Machine method when using linear kernels and RBF. The results of the Support Vector Machine linear kernel accuracy of 79.66% and an increase of 88.01% after using the ensemble. While the accuracy for the Support Vector Machine kernel RBF is 79.51 and an increase of 88.04% after using the ensemble.
Co-Authors Firman Aziz Jeffry Jeffry Nur Ayu Asrhi Syahrul Usman