PERAMALAN TRAFIK UNTUK USER LONG TERM EVOLUTION DENGAN MOBILITAS RANDOM WALK MENGGUNAKAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE

DICKY, BAGUS TANGGARA (2019) PERAMALAN TRAFIK UNTUK USER LONG TERM EVOLUTION DENGAN MOBILITAS RANDOM WALK MENGGUNAKAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE. Undergraduate Thesis thesis, Institut Telkom Purwokerto.

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Abstract

ABSTRACT The rapid development of technology has become an important guideline for everyone competing to produce the best communication solutions. The development in telecommunications has reached the next generation, namely the fourth generation (4G) or better known as LTE. Long Term Evolution is an improvement of the 3GPP (3rd Generation Partnership Program) consortium. Seeing the growth of Long Term Evolution traffic and to predict this growth, forecasting is made to predict the future. The method used for forecasting uses the Autoregressive Integrated Moving Average. With the forecasting analysis method using a model (1,1,0) to create the ARIMA equation. By simulating RSRP and SINR traffic as many as 15 Iterations with 30 users. The results of ARIMA predictions continue to grow on average and Minimum Mean Square Mean The overall error in RSRP traffic is 62.6081 and SINR traffic is 49.9601. Keywords: ARIMA, LTE, RSRP, SINR

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