AGRISE
Vol 19, No 3 (2019): AUGUST

Forecasting of Indonesia Seaweed Export: A Comparison of Fuzzy Time Series with and without Markov Chain

Andi Sri Bintang (Brawijaya University and National Pingtung University of Science and Technology)
Wen-Chi Huang (National Pingtung University Science and Technology)
Rosihan Asmara (Faculty Agriculture Brawijaya University)

Article Info

Publish Date
26 Aug 2019

Abstract

This study compared Fuzzy Time Series with and without Markov Chain Method for forecasting Indonesian seaweed export in particular; it analyzed the forecasting ability of the models and the effects of different lengths of interval and increment information on the forecasting error of models. The secondary data between 1989 and 2018 were collected from Bureau Central Statistic (BPS), UN Comtrade, Ministry Marine and Fisheries (KKP). The results indicate that Fuzzy Time Series with and without Markov Chain method performs better in the forecasting ability in short-term period prediction and the values of Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) tends to be smaller than the Fuzzy Time Series without Markov Chain.

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Journal Info
AGRISE
Website

Abbrev

AGRISE

Publisher

Universitas Brawijaya

Subject

Agriculture, Biological Sciences & Forestry Economics, Econometrics & Finance

Description

AGRISE adalah Jurnal Sosial Ekonomi Pertanian yang berada di lingkungan Fakultas Pertanian Universitas Brawijaya yang berupa hasil penelitian, studi kepustakaan maupun tulisan ilmiah terkait. Jurnal ini diterbitkan pertama kali pada tahun 2001 oleh Jurusan Sosial Ekonomi Pertanian FPUB. Pada tahun ...