Analisis Simulasi Model COST-231 Multiwall Pathloss Indoor Berbasis Wireless Sensor Network pada Aplikasi Absensi Mahasiswa dengan Tag RFID Menggunakan RPS (Radiowave Propagation Simulator)
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Abstract
Wireless Sensor Network is a solution to solve cable-based network problems especially in attendance applications with RFID Tag. However, in this research, RFID Tag based on Wireless Sensor Network is implemented in indoor conditions that have higher path loss than in outdoor conditions. This paper analyzed the distribution of RSSI receipt of indoor COST231 Multiwall path loss model by using Radiowave Propagation Simulator (RPS) to model the indoor condition of the building as the actual conditions such as the size and the building materials. This Simulation use 3 Node Router and 8 End node of Wifi RFID Reader with WLAN 1EEE 802.11.n communication protocol at 2.4 GHz frequency. The simulation result shows that the mean and deviation standard values of RSSI at the scenario router node plus end node implemented condition is -46.94 dBm and 10,79, respectively.
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Wireless Sensor Network adalah solusi dalam mengatasi masalah jaringan berbasis kabel terutama dalam aplikasi absensi mahasiswa dengan Tag RFID. Namun, pada studi ini, wireless sensor network diimplementasikan pada kondisi indoor yang memiliki pathloss lebih tinggi dibandingkan pada kondisi outdoor. Penelitian ini menganalisis sebaran daya terima RSSI pada simulasi model indoor path loss COST231 Multiwall dengan menggunakan Radiowave Propagation Simulator (RPS) untuk memodelkan kondisi indoor gedung sesuai dengan kondisi sebenarnya, baik dari ukuran maupun bahan gedung. Simulasi menggunakan 3 Node Router dan 8 End node dari Wifi RFID Reader dengan protocol komunikasi WLAN 1EEE 802.11.n pada frekuensi 2,4 GHz. Hasil simulasi menunjukkan bahwa nilai rata-rata dan standar deviasi RSSI pada kondisi terimplementasi dari router node dan end node adalah -46,94 dBm dan 10,79 secara berturut-turut.
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References
Amanaf, M. A., Danisya, A. R., & Rodian, R. (2017). Analisis Perbandingan Pemodelan Pathloss COST-231 Hata dan Walfisch Ikegami Terhadap Pathloss Pengukuran dengan Metode Drive Test di Wilayah. Jurnal Infotel, 9(4).
Amanaf, M. A., Setijadi, E., & Suwadi. (2013). Implementasi Sistem Akuisisi Data pada Bridge Sructural Health Monitoring dengan Jaringan Sensor Nirkabel. In Proceeding Seminar Ilmu Pengetahuan Teknik 2013 LIPI-PPET (pp. 428–432).
Buratti, C., Conti, A., Dardari, D., & Verdone, R. (2009). An overview on wireless sensor networks technology and evolution. Sensors, 9(9), 6869–6896. https://doi.org/10.3390/s90906869
Cesar, J., & Leon, A. (2015). Evaluation of IEEE 802.11ah Technology for Wireless Sensor Network Applications. Tampere University of Technology. Retrieved from https://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/22799/Araiza Leon.pdf;sequence=1
Flattie, A. G. (2012). Optimizing the Existing Indoor Propagation Prediction Models. International Conference on Wireless Networks (ICWN 2012), 49(Icwn), 202–207. https://doi.org/10.7763/IPCSIT.2012.V49.37
He, D., Mujica, G., Liang, G., Portilla, J., & Riesgo, T. (2014). Radio propagation modeling and real test of ZigBee based indoor wireless sensor networks. Journal of Systems Architecture, 60(9), 711–725. https://doi.org/10.1016/j.sysarc.2014.08.002
Heereman, F., Joseph, W., Tanghe, E., Plets, D., Verloock, L., & Martens, L. (2012). Path loss model and prediction of range, power and throughput for 802.11n in large conference rooms. AEU - International Journal of Electronics and Communications, 66(7), 561–568. https://doi.org/10.1016/j.aeue.2011.11.008
Kaur, K., Kaur, P., & Singh, E. S. (2014). Wireless Sensor Network : Architecture , Design Issues and Applications. International Journal of Scientific Engineering and Research (IJSER), 2(11), 6–10.
Kurt, S., & Tavli, B. (2017). Path-Loss Modeling for Wireless Sensor Networks: A review of models and comparative evaluations. IEEE Antennas and Propagation Magazine, 59(1), 18–37. https://doi.org/10.1109/MAP.2016.2630035
Mahyu, T. A., Norma, A., & Amanaf, M. A. (2017). Perancangan dan Analisis Jaringan Indoor Femtocell LTE 2300 MHz di Gedung Java Heritage Hotel Purwokerto dengan Menggunakan Radiowave Propagation Simulator. In CITEE 2017 (Vol. 2, pp. 34–41).
Olasupo, T. O., Otero, C. E., Olasupo, K. O., & Kostanic, I. (2016). Empirical path loss models for wireless sensor network deployments in short and tall natural grass environments. IEEE Transactions on Antennas and Propagation, 64(9), 4012–4021. https://doi.org/10.1109/TAP.2016.2583507
Sarka, A., Majumdar, S., & Bhattacharya, P. P. (2013). Path Loss Estimation for a Wireless Sensor Network for Application in Ship. International Journal of Computer Science and Mobile Computing, 2(6), 87–96.
Scholastica, N. (2014). Pathloss Prediction Model of a Wireless Sensor Network in an Indoor Environment. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(9), 11665–11673.
Setijadi, E., & Amanaf, M. A. (2013). Design of Large Scale Structural Health Monitoring System for Long-Span Bridges Based on Wireless Sensor Network. In ICAST UBIMEDIA (International Joint Conference on Awareness Science and Technology & Ubi-Media Computing ) (pp. 169–174).
Solahuddin, Y. F., & Mardeni, R. (2011). Indoor empirical path loss prediction model for 2.4 GHz 802.11n network. Proceedings - 2011 IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2011, (2), 12–17. https://doi.org/10.1109/ICCSCE.2011.6190487
Wicaksono, F. A., Dirgantoro, B., Mt, I., Michrandi, S., & St, N. (2015). Perancangan dan Prototipe Aplikasi Presensi Perkuliahan dengan Menggunakan Android pada Wireless Sensor Network. E-Proceeding of Engineering, 2(1), 619–624.