Akses terbuka Jurnal
Dinamika dan Probabilitas Transisi Curah Hujan Harian di MKG Itera Menggunakan Model Rantai Markov
Indonesian Journal of Applied Mathematics · Vol. 6 No. 1 (2026) · hlm. 49–57
- ISSN
- 2774-2016, 2774-2067
- Terbit
- 2026-04-30
- Penerbit
- Institut Teknologi Sumatra
Abstrak
This study aims to analyze the characteristics of daily rainfall in the Meteorology, Climatology, and Geophysics (MKG) Itera region during the period from January to October 2025 using a Markov Chain model. Daily rainfall data are classified into four states based on rainfall intensity, namely No Rain, Light Rain, Moderate Rain, and Heavy Rain. The analysis begins with descriptive statistics to identify general characteristics of the data. The average daily rainfall is 6.50 mm/day, with the highest recorded intensity reaching 82.8 mm on February 21, 2025, and a rainfall variance of 195.68 mm². Subsequently, a transition probability matrix is constructed to model the dynamics of rainfall condition changes between states from day to day. In addition, the steady-state probabilities are calculated to determine the long-term tendencies of rainfall conditions. The results indicate that daily rainfall exhibits a fluctuating pattern with relatively high variability. Most observations fall into the No Rain (48%) and Light Rain (40%) states, indicating that more than 88% of rainfall conditions are of low intensity. The transition probability matrix shows that the highest transition probability occurs from Moderate Rain to Light Rain at 66.7%, suggesting that moderate rainfall tends to decrease to light rainfall on the following day. Furthermore, the probabilities of remaining in the No Rain and Light Rain states are relatively high, at 61.1% and 46.7%, respectively, indicating persistence in dry or low-intensity rainfall conditions. The steady-state distribution shows that, in the long run, the probabilities are 47.6% for No Rain, 40.4% for Light Rain, 8.9% for Moderate Rain, and 3.0% for Heavy Rain. These findings suggest that rainfall patterns in the MKG Itera region are predominantly characterized by dry to low-intensity conditions. Overall, the Markov Chain model is capable of effectively representing the dynamics of daily rainfall and provides a comprehensive description of long-term rainfall characteristics in the MKG Itera region.
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- State University of Semarang
- Bandung Institute of Technology
- Universitas Halu Oleo
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Tampilkan sebagai tabel
| Rekan penulis | Organisasi | Artikel bersama |
|---|---|---|
| Danni Gathot Harbowo | Afiliasi tidak diketahui | 2 |
| Sri Sulistyorini | State University of Semarang | 2 |
| Intan Tamara Azka Zanuba | Afiliasi tidak diketahui | 1 |
| Zinni Fitriasih | Afiliasi tidak diketahui | 1 |
| Lestari Citra Alini | Afiliasi tidak diketahui | 1 |
| Dewi Suhika | Bandung Institute of Technology | 1 |
| Sri Efrinita Irwan | Afiliasi tidak diketahui | 1 |
| Edi Cahyono | Universitas Halu Oleo | 1 |
| . Kartono | Afiliasi tidak diketahui | 1 |
| Fuji Lestari | Afiliasi tidak diketahui | 1 |
| Mika Alvionita S | Afiliasi tidak diketahui | 1 |
| Ardika Satria | Afiliasi tidak diketahui | 1 |
| Nabila Nurita Putri | Afiliasi tidak diketahui | 1 |
| Muhammad Ammar Alkautsar | Afiliasi tidak diketahui | 1 |
| Sekar Anisa Sely | Afiliasi tidak diketahui | 1 |
| Della Najunda K.S | Afiliasi tidak diketahui | 1 |
| Rofi Ilmi Fadhillah | Afiliasi tidak diketahui | 1 |
| Alfredo Edward Lazuardi | Afiliasi tidak diketahui | 1 |
| Andre Markus Fernando Lubis | Afiliasi tidak diketahui | 1 |
| Juan Daniel Turnip | Afiliasi tidak diketahui | 1 |
| Erina Rosalia Irda | Afiliasi tidak diketahui | 1 |
| Adelia Azahra | Afiliasi tidak diketahui | 1 |
| Yanti Marito | Afiliasi tidak diketahui | 1 |
| Meysi Supmawati | Afiliasi tidak diketahui | 1 |
| Eli Rahmawati | Afiliasi tidak diketahui | 1 |
| Naila Tsamrotul Aula | Afiliasi tidak diketahui | 1 |
| Barokah Isdaryanti | State University of Semarang | 1 |
| Farid Ahmadi | Afiliasi tidak diketahui | 1 |
| ANGGI CINTYA LESTARI | Afiliasi tidak diketahui | 1 |
| Aldina Eka Andriani | Afiliasi tidak diketahui | 1 |
| Dewi Nilam Tyas | Afiliasi tidak diketahui | 1 |
| Sri Hartati | Afiliasi tidak diketahui | 1 |
| Isti Nur Hayanah | Afiliasi tidak diketahui | 1 |
| Wahana Adinindya Nugrahaeni | Afiliasi tidak diketahui | 1 |
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