Model Multi Layer Perceptron untuk Indoor Positioning System Berbasis Wi-Fi
Copyright (c) 2017 Jurnal Teknologi dan Sistem Komputer
Indoor positioning system issue is an open problem that still needs some improvements. This research explores the utilization of multi layer perceptron in determining someone’s position inside a building or a room, which generally known as Indoor Positioning System. The research was conducted in some steps: dataset normalization, multi layer perceptron implementation, training process of multi layer perceptron, evaluation and analysis. The training process has been conducted many times to find the best parameters that produces the best accuracy rate. The experiment produces 79,16% as the highest accuracy rate. Compared to previous research, this result is comparably lower and needs some parameters tweaking or changing the neural networks architectures.
Masalah penentuan posisi di dalam ruangan masih memerlukan banyak perbaikan. Penelitian ini mencoba melakukan eksplorasi terhadap penggunaan multi layer perceptron untuk penentuan posisi seseorang di dalam gedung atau ruangan, yang lebih dikenal dengan istilah Indoor Positioning System. Penelitian ini dilaksanakan dalam beberapa tahap yaitu normalisasi dataset, implementasi multi layer perceptron, pelatihan multi layer perceptron dan proses pengujian serta analisis. Proses pelatihan dilakukan beberapa kali untuk menemukan parameter-parameter yang menghasilkan akurasi terbaik. Dari hasil percobaan yang dilakukan didapatkan tingkat akurasi terbaik sebesar 79,16%. Hasil tersebut masih lebih rendah jika dibandingkan dengan hasil penelitian sebelumnya, sehingga memerlukan perubahan pengaturan parameter atau pengubahan arsitektur jaringan syaraf tiruan yang digunakan.
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