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All Journal Mathematical Journal of Modelling and Forecasting
Pratama, Tasya Putri
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Forecasting Rainfall in Padang Panjang City Using Fuzzy Time Series Cheng Pratama, Tasya Putri; Sari, Devni Prima
Mathematical Journal of Modelling and Forecasting Vol. 3 No. 1 (2025): June 2025
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v3i1.35

Abstract

Rainfall is essential in many areas of life, including agriculture, water resource management, and disaster mitigation.  Padang Panjang is one of the cities with high rainfall. Rainfall varies throughout the year, affecting agriculture and people's livelihoods. Therefore, accurate rainfall estimation is required to support effective planning and management. This study aims to forecast the amount of rainfall in Padang Panjang City from January 2020 to November 2024 using the fuzzy time series method of the Cheng model. The data is on the monthly rainfall amount from January 2020 to November 2024, obtained from the BMKG Padang Pariaman Climatology Station. The stages in the fuzzy time series Cheng model are forming the universe set, forming intervals, fuzzifying the data, analyzing Fuzzy Logical Relationship (FLR) and Fuzzy Logical Relationship Group (FLRG), determining the weight of the relationship, forecasting, and measuring the accuracy of predicting using Mean Absolute Percentage Error (MAPE). The forecasting results were validated using MAPE, with a value of 41%, which indicates that the model is feasible. The forecasting results for the following three periods are December 2024 high rainfall, January 2025 medium rainfall, and February 2025 high rainfall. This research shows that the fuzzy time series method of the Cheng model can be used as an alternative means of forecasting time series data.
Co-Authors Devni Prima Sari