komparasi metode anfis dan fuzzy time series kasus peramalan jumlah wisatawan australia ke bali

komparasi metode anfis dan fuzzy time series kasus peramalan jumlah wisatawan australia ke bali

;IDA BAGUS KADE PUJA ARIMBAWA K.;KETUT JAYANEGARA;I PUTU EKA NILA KENCANA
brain: broad research in artificial intelligence and neuroscience 2013 Vol. 2 pp. 18-26
156
k.2013e-jurnalkomparasi

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%

Citation

ID: 227291
Ref Key: k.2013e-jurnalkomparasi
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
227291
Unique Identifier:
10.24843/MTK.2013.v02.i02.p033
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet