dc.contributor.author | RAMADHANI, Lutvia C. | |
dc.contributor.author | ANGGRAENI, Dian | |
dc.contributor.author | KAMSYAKAWUNI, Ahmad | |
dc.contributor.author | HADI, Alfian Futuhul | |
dc.date.accessioned | 2020-11-18T04:18:48Z | |
dc.date.available | 2020-11-18T04:18:48Z | |
dc.date.issued | 2018-04-27 | |
dc.identifier.uri | http://repository.unej.ac.id/handle/123456789/102047 | |
dc.description | The 1st International Conference of Combinatorics, Graph Theory, and Network Topology 25–26 November 2017, The University of Jember, East Java, Indonesia | en_US |
dc.description.abstract | This paper presents a forecast model of Saxena-Easo fuzzy time series
prediction to study the prediction of Indonesia inflation rate in 1970-2016. We use
MATLAB software to compute this method. The algorithm of Saxena-Easo fuzzy
time series doesn’t need stationarity like conventional forecasting method, capable of
dealing with the value of time series which are linguistic and has the advantage of
reducing the calculation, time and simplifying the calculation process. Generally it’s
focus on percentage change as the universe discourse, interval partition and
defuzzification. The result indicate that between the actual data and the forecast data
are close enough with Root Mean Square Error (RMSE)= 1.5289. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IOP Conf. Series: Journal of Physics: Conf. Series 1008 (2018) 012021 | en_US |
dc.subject | algorithm | en_US |
dc.subject | saxena-easo fuzzy time series | en_US |
dc.title | An Algorithm of Saxena-Easo on Fuzzy Time Series Forecasting | en_US |
dc.type | Article | en_US |
dc.identifier.kodeprodi | kodeprodi1810101#Matematika | |
dc.identifier.nidn | NIDN0016028201 | |
dc.identifier.nidn | NIDN0029117202 | |
dc.identifier.nidn | NIDN019077403 | |