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Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia

T. H. F. Harumy, Lubis Akhyar, and Iqbal Muhammad
Computer Science, University Pembangunan Pancabudi, Medan, Indonesia
Abstract—Artificial Neural Network Backpropogation is used to measure the Utilization Priority of BTS (Base Transceiver Station) to Optimize Telecommunication in 3T Disadvantaged, Outermost, Inside Areas based on 7 variables that are dujikan namely Population Density / thousand, User / User, Climate / Geography (Air temperature, rainfall, altitude), Environment, Culture / Community Attitudes, Cost of manufacture / billion, service range. By using Backpropogation method finally found the best architectural pattern yatu architecture 7 - 7 - 1 from 3 architecture which have been tested. MSE obtained for Trainning of 0.0001000609 and MSE testing of 0,0027164812 and Epoch obtained is 2164 From the pattern is then predicted telecommunication network users in 2017 that is equal to 317.912.790 million soul, and from the variables that become input the measurement was obtained that the polewali mandar village variable is the priority village of installation of BTS (Base Transceiver Station) with value 0.9298 next is South Nias district with value 0.9242, West Nias 0.9055, Sorong 0.8860, and Sorong jaya 0.8569.

Index Terms—neural network, backpropogation, BTS, village

Cite: T. H. F. Harumy, Lubis Akhyar, and Iqbal Muhammad, "Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia," International Journal of Electronics and Electrical Engineering, Vol. 6, No. 3, pp. 43-47, September 2018. doi: 10.18178/ijeee.6.3.43-47
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