Penerapan Rantai Markov Dalam Peramalan Cuaca  (Studi Kasus: Cuaca Harian Di Deli Serdang)

Alio Hutaperi Siboro; Christina N Simanjuntak; Maria Ayuni Isabella Manullang; Natalia Anggriani Simanjuntak; Santa Falare Sitanggang; Taing Pebrieni Simbolon; Sudianto Manullang; Alvi Sahrin Nasution

doi:10.31004/innovative.v5i3.19426

Authors

Alio Hutaperi Siboro Universitas Negeri Medan
Christina N Simanjuntak Universitas Negeri Medan
Maria Ayuni Isabella Manullang Universitas Negeri Medan
Natalia Anggriani Simanjuntak Mahasiswa
Santa Falare Sitanggang Universitas Negeri Medan
Taing Pebrieni Simbolon Mahasiswa
Sudianto Manullang Universitas Negeri Medan
Alvi Sahrin Nasution Universitas Negeri Medan

DOI:

https://doi.org/10.31004/innovative.v5i3.19426

Abstract

Weather is the state of the air (about temperature, sunlight, humidity, wind speed, and so on) in a certain place with a limited period of time (KBBI). Daily weather forecasting holds significant importance in daily activities, especially in helping people and various industrial sectors adapt their activities to upcoming weather conditions. The objective of this research is to apply the Markov Chain model in daily weather forecasting in Deli Serdang. This study uses daily weather data in Deli Serdang district from March 1, 2025 to April 30, 2025. The data was sourced from the Meteorology, Climatology, and Geophysics Agency (BMKG). The research variables used are weather conditions, namely, sunny , cloudy , light rain , and rain Weather predictions for the next seven days can be carried out gradually by taking into account previous weather conditions. The results of the forecasting obtained show that the chances of each weather condition occurring in the following days can be clearly mapped, thus providing a more realistic probabilistic picture than conventional deterministic methods.

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