Pemanfaatan sistem Brain-Computer Interface (BCI) sebagai penghubung pikiran manusia dengan peralatan eksternal sangat bergantung pada keakuratan pengklasifikasian dan pengidentifikasian sinyal EEG khususnya gerak motor imagery. Kesuksesan deep learning, sebagai contoh Convolutional Neural Network (CNN), dalam proses klasifikasi pada berbagai bidang berpeluang untuk diimplementasikan pada klasifikasi gerak motor imagery. Pengimplementasian CNN untuk klasifikasi sinyal EEG motor imagery (MI-EEG) gerakan jari tangan diperkenalkan dalam tulisan ini. Rancangan sistem klasifikasi terdiri dari dua bagian yaitu convolution layer dan multilayer perceptron yang diimplementasikan menggunakan Python 3.7 dengan library TensorFlow 2.0 (Keras). Pengujian rancangan sistem dilakukan terhadap lima subjek dari data MI-EEG 5F dengan frekuensi pencuplikan 200 Hz. Pengujian melibatkan Kfold-cross validation dan analisis pada confusion matrix. Berdasarkan hasil pengujian, peningkatan ukuran kernel menghasilkan peningkatan rata-rata akurasi sistem. Sistem dengan akurasi terbaik diperoleh pada rancangan dengan jumlah kernel 50 sebesar 51,711%. Rancangan sistem menghasilkan kinerja yang melebihi hasil penelitian yang menjadi rujukan utama.
At present the need for integrated data communication has become a major need for an office, especially at this time it tends to have many branch offices to support its business processes. Problems will arise if the head office has a branch office in a different city. Such as more costs in building network infrastructure to connect between headquarters and branches. One solution is to use Ethernet Over IP (EoIP) Tunnel. That is one of the tunneling features of the Mikrotik that provides an efficient solution to this problem. Network tunnel that is built between Mikrotik devices over TCP / IP. In running EoIP tunnel simulation using IPv4 to communicate with each other. Ethernet Over IP (EoIP) is a proprietary protocol, which is only owned by MikrotikOS. The routing protocol used in the EoIP tunnel is OSPF. Open Shortest Path First (OSPF) is one dynamic routing protocol (Dynamic Routing) that is able to maintain, manage and distribute routing information between networks following any dynamic network changes. Then the quality of service is observed with throughput and packet loss parameters. The results of throughput parameters, the performance of video streaming services reaches 280.45 kbits / Sec. In the video streaming communication service, the average OSPF EoIP Tunnel packet loss reaches 0.92%.
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