English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper aimed to elaborates and compares the performance of Fuzzy Time Series ( FTS ) model with Markov Chain ( MC ) model in forecasting the Gross Regional Domestic Product ( GDRP ) of Bali Province.  Both methods were considered as forecasting methods in soft modeling domain.  The data used was quarterly data of Bali’s GDRP for year 1992 through 2013 from Indonesian Bureau of Statistic at Denpasar Office.  Inspite of using the original data, rate of change from two consecutive quarters was used to model. From the in-sample forecasting conducted, we got the Average Forecas­ting Error Rate ( AFER ) for FTS dan MC models as much as 0,78 percent and 2,74 percent, respec­tively.  Based-on these findings, FTS outperformed MC in in-sample forecasting for GDRP of Bali’s data.

KOMPARASI KINERJA FUZZY TIME SERIES DENGAN MODEL RANTAI MARKOV DALAM MERAMALKAN PRODUK DOMESTIK REGIONAL BRUTO BALI