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PERBANDINGAN FUZZY TIME SERIES MARKOV CHAIN DAN FUZZY TIME SERIES CHENG | Atmawanti | Jurnal Gaussian skip to main content

PERBANDINGAN FUZZY TIME SERIES MARKOV CHAIN DAN FUZZY TIME SERIES CHENG

Indira Irma Atmawanti  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
*Arief Rachman Hakim  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tarno Tarno  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2024 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Investing is a hot and fast-growing topic right now. Stock.investing.is one of the most popular investments by the public. The JCI is an index that measures the performance of all stocks listed on the IDX. The closing price of the stock is published daily and can be used by investors as an investment benchmark. The occurrence of stock price fluctuations entails a high risk of loss. Predicting stock prices is one way to avoid this risk. Fuzzy time series is a time series model that can be used to minimize the risk of future occurrences. Time parameter data is not stationary, so this research uses fuzzy time series with Markov chains and Cheng's method to determine the JCI completion dates from January 2018 to June 2022. Calculating the accuracy level of the two method approaches using symmetric Mean Absolute Percentage Error (sMAPE), the sMAPE value obtained in the Fuzzy Time Series Markov Chain method is 2.11% and the Fuzzy Time Series Cheng method is 2.98%. The conclusion is that of the two methods the Markov Chain has a smaller value and can be said to be a better method compared to the Cheng method.

 

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Keywords: Fuzzy time series; Markov Chain; Cheng; sMAPE

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