Penerapan Rantai Markov Dalam Peramalan Cuaca (Studi Kasus: Cuaca Harian Di Deli Serdang) - Siboro, Alio Hutaperi; N Simanjuntak, Christina; Manullang, Maria Ayuni Isabella; Simanjuntak, Natalia Anggriani; Sitanggang, Santa Falare; Simbolon, Taing Pebrieni; Manullang, Sudianto; Nasution, Alvi Sahrin (Innovative: Journal Of Social Science Research, 2025)
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.