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All Journal Dimas: Jurnal Pemikiran Agama untuk Pemberdayaan Kubik IJoICT (International Journal on Information and Communication Technology) TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika KUBIK: Jurnal Publikasi Ilmiah Matematika
Martina, Annisa
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Mathematics Social Sciences Other

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PERBANDINGAN METODE FUZZY TIME SERIES MARKOV CHAIN DAN FUZZY TIME SERIES CHENG UNTUK PERAMALAN DATA INFLASI Martina, Annisa; Noor Sa’adah, Fuziani; Fatchul Huda, Arief
TEKTRIKA Vol 9 No 1 (2024): TEKTRIKA Vol.9 No.1 2024
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v9i1.6914

Abstract

The value of inflation can determine decision-making for economic actors. Therefore, in order for entrepreneursto plan their business well, accurate inflation forecasting is necessary. Fuzzy Time Series (FTS) is a concept tosolve forecasting problems if historical data is formed into linguistic values. This method has advantages, namelythe calculation process does not require a complex system and is able to solve the problem of forecasting historicaldata in the form of linguistic values. Fuzzy Time Series Cheng (FTS-Cheng) method has a slightly differentmethod of determining intervals, while the interval determination in Fuzzy Time Series Markov Chain (FTS-MC)method is the same as other FTS methods. FTS-MC is a combined method of FTS with Markov chain stochasticprocesses. In this paper, we discuss forecasting inflation data using FTS-MC and FTS-Cheng methods. This studyuses monthly data on Indonesian inflation from January 2017 to December 2021. FTS-MC method has a MAPEvalue of 9.41% and FTS-Cheng method has a MAPE value of 32.25%. Based on the criteria for the accuracy ofMAPE, the forecasting value using FTS-MC method meets the very good forecasting results and the forecastingresults using FTSC method meet the sufficient forecasting results. Based on the MAPE value obtained, a betterforecasting method for the case study of Indonesian inflation data in 2017-2022 is FTS-MC method.
Co-Authors Arief Fatchul Huda, Arief Asep Solih Awalluddin, Asep Solih Dewi, Apianti Setia Girana, Irwan Jajuli, Marsa Aufa lia kamelia Noor Sa’adah, Fuziani Ramdani Wahyu Sururie Rini Cahyandari Rohmanur Aziz, Rohmanur