Rainfall Prediction Analysis Using the Fuzzy Time Series Method in Medan City

Authors

  • Syaftial Zikri Universitas Muhammadiyah Sumatera Utara
  • Wilda Rina Hasibuan Universitas Muhammadiyah Sumatera Utara

DOI:

https://doi.org/10.59934/jaiea.v4i1.685

Keywords:

rainfall, fuzzy time series, Chen method, forecasting

Abstract

The increasingly significant climate change causes high rainfall variability, thus requiring an accurate prediction method for disaster mitigation planning and water resource managment. This study aim to analyze rainfal prediction in Medan City using Fuzzy Time Series (FTS) methode. Historical rainfall data for Medan City for a certain period is collected and processed to build an FTS model. The fuzzification process is carried out to convert numerical data into fuzzy values, then the time series relationship is identified to predict the next rainfall value. Based on Chen's fuzzy time series with the detemination of the average-based interval, the Medan City rainfall forecast based on January 2019-December 2023 data obtained the forecast results for January 2024 is 386.7 mm. From the result of tests that have caried out, the best number of sampels be used in the Medan City rainfall case is 60 data, namely the period January 2019 - December 2023.

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Published

2024-10-15

How to Cite

Zikri, S., & Hasibuan, W. R. (2024). Rainfall Prediction Analysis Using the Fuzzy Time Series Method in Medan City. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 4(1), 575–579. https://doi.org/10.59934/jaiea.v4i1.685