komparasi metode anfis dan fuzzy time series kasus peramalan jumlah wisatawan australia ke bali
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ID: 227291
2013
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Abstract
This study compares the accuracy of forecasting using ANFIS and Fuzzy Time Series the number of Australian tourists to Bali. The data used in this study are data on the number of Australia tourists visit to Bali from the period January 2006 through December 2011. ANFIS consists of two stages of learning and testing phases. Least Squares Estimator is used to study the forward direction and Error Back Propagation learning is used in the reverse direction. Forecasting with Fuzzy Time Series is forecast to capture the pattern of previous data is then used to project the data to come. The results of comparison of both methods showed that the ANFIS method has a higher forecasting accuracy than the method of Fuzzy Time Series. Forecasting by using ANFIS method obtained AFER aqual to 9,26% while the prediction using the method of Fuzzy Time Series obtained AFER aqual to 14,02%
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| Reference Key |
k.2013e-jurnalkomparasi
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|---|---|
| Authors | ;IDA BAGUS KADE PUJA ARIMBAWA K.;KETUT JAYANEGARA;I PUTU EKA NILA KENCANA |
| Journal | brain: broad research in artificial intelligence and neuroscience |
| Year | 2013 |
| DOI |
10.24843/MTK.2013.v02.i02.p033
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| URL | |
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