aplikasi algoritma genetika untuk meramalkan konsumsi premium kota denpasar

aplikasi algoritma genetika untuk meramalkan konsumsi premium kota denpasar

;VICTOR MALLANG;KETUT JAYANEGARA;NI MADE ASIH;I PUTU EKA N. KENCANA
brain: broad research in artificial intelligence and neuroscience 2014 Vol. 3 pp. 160-167
201
mallang2014e-jurnalaplikasi

Abstract

This research aimed to forecast the gasoline demand at Denpasar using genetic algorithm method. This  algorithm was selected because of easy to implement and its ability to find acceptable solution quickly.  This algorithm works by searching the best individu according to fitness function defined. The series data used in the research were 60 observations of monthly gasoline demand at Denpasar for period January 2009 through December 2013.  By observing the Partial Autocorrelation Function (PACF) plot, we found the last lag before the series become stationer was sixth lag.  Based on this finding, we decided the best individu was represented by six genes. This individu, in addition, was used to make in-sample forecasting.  The forecasted data had mean absolute error (MAE) as much as 553,27 kiloliters.  For one semester out-of sample forecast, we found gasoline consumption fluctuated with lowest and highest consumption were for February 2014 and June 2014, respectively.

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0x95644003c57E6F55A65596E3D9Eac6813e3566dA
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177485
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10.24843/MTK.2014.v03.i04.p079
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