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All Journal UNP Journal of Statistics and Data Science
Tsani, Nahda Maesya
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Penerapan Rantai Markov pada Data Curah Hujan Harian di Kota Semarang Tsani, Nahda Maesya; Permana, Dony; Kurniawati, Yenni; Salma, Admi
UNP Journal of Statistics and Data Science Vol. 2 No. 3 (2024): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol2-iss3/189

Abstract

Rainfall is a measure of the amount of water that falls on the earth's surface in a given period of time. High rainfall can cause flooding in certain areas, while low rainfall can leave areas vulnerable to drought. Semarang City is one of the largest cities in Java Island that is often hit by floods. Efforts can be made to anticipate the risk of flooding, one of which is by studying the pattern of rainfall. This study will determine the chances of rainfall transition in Semarang City in steady state conditions using Markov chains. The results are expected to be used to anticipate the risk of flooding in Semarang City. The probability of daily rainfall transition in Semarang City in each state for the next period of time is 90.5% chance of staying in the light rain state, 7.97% chance of staying in the medium rain state and 1.50% chance of staying in the heavy rain state.
Co-Authors Permana, Dony Salma, Admi Yenni Kurniawati