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MARKOV CHAIN ANALYSIS FOR PREDICTION OF MONTHLY AVERAGE TEMPERATURE PATTERNS AT PATTIMURA METEOROLOGICAL STATION AMBON 2015 - 2024 Selangur, Djudid Sintje; Lestaluhu, Musfa Rizaldi; Qadry, Alwatia Al; Huwae, Angel Gressovin; Toumahuw, Imanuella; Lewen, Dorothy H.; Seknun, Fitri R.; Namkatu, Jalianti; Yudistira, Yudistira
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 2 (2025): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol7iss2page199-208

Abstract

Weather has a significant impact on human activities, making accurate weather forecasting an important necessity. This study aims to analyze the patterns of climate element changes at the Pattimura Ambon Meteorological Station using the Markov Chain approach to identify climate transition patterns, estimate steady-state time, and predict the climate in 2025. Monthly secondary climate element data for the period 2015-2024 were obtained from the Maluku Province BPS, categorized into three conditions: cold (<25°C), normal (25°C-26.5°C), and hot (>26.5°C). The data were analyzed using the Markov Chain method with calculations of the transition probability matrix, matrix convergence, and steady-state distribution. The research results indicate that the system reaches equilibrium after 47 periods with a long-term distribution: cold condition 2.85%, normal 35.66%, and hot 61.76%. The hot condition has the highest stability with a probability of remaining in the same state at 91.8%. The 2025 prediction indicates that monthly temperature probabilities gradually move toward the steady-state distribution, illustrating the dominance and persistence of hot conditions in the long term. The analysis results provide important implications for agricultural planning, tourism, infrastructure, and disaster mitigation in the city of Ambon in the face of climate change.
Co-Authors Abdullah, Salma Adnan, Muh. Akbar, Fauzia Alfian Allen, Rio Valery Ampauleng, Ampauleng Anindya, Anindya Ansory, Ahmad Anto, Ahmad Apriyanti, Maulita Dwi Ardani, Farell Ari Andayani Ayuningsih, Fitria Balami, A. M. Batubara, Fanny Yuliana Cupian da Costa, Julieta Darman, Luky Prassetya Deded Chandra Defrian, Angga Dino Caesaron Djinis, Musdar Effy Dussy, Achmad Nur Azhary Effy Djinis, Musdar Effy Djinis Ernita, Yuni Fathur Rizal Ferry Kondo Lembang H Hasmawati Hakim, Irfan Halim, Ardiansyah Hasibuan, Melkisedek Hasman, Elvin Hasyim, Fuadz Hatala, Devita Haumahu, G. Hendrawan, Kevin Anggakusuma Herdian, Fithra Husnah, Maulida Huwae, Angel Gressovin Ilma Mufidah Irma Setiawan, Irma J. Djami, Ronald J. Wattimanela, Henry Jusmaldi Jusmaldi Kilikily, Aditia Rajasa Kifta L, Rosanti Laamena, Novita S. Laamena, Novita Serly Laode Muhammad Harjoni Kilowasid Latupeirissa, S. J. Lembang, F. K. Lestaluhu, Fitri Lestaluhu, Musfa Rizaldi Lewaherilla, Norisca Lewen, Dorothy H. Lexy Janzen Sinay, Lexy Janzen Loklomin, S. B Loklomin, S. B. Lusye Bakarbessy Mahubessy, Juan Felix Benicktus Malik, Kamil Malrianti, Yefsi Manalu, Omena Maswahenu, Mara Matdoan, M. Y. Ma’bar, M. Fadin Medi Hendra, Medi Muhammadin, Akhmad Musa Namkatu, Jalianti Nanlohy, Y. W. A. Ni Made Ari Suryathi Ningsi, Fitri Wahyu Noven, Sarah Annisa Nurinayah, Sevi Palisoa, N. F. Qadry, Alwatia Al Rahma, Ayu Dyah Rahmaniar, Wa Ode Rifdian, Filandia Rosalina Salhuteru S Laamena, Novita Safitri, Yuniar Andini Sedubun, Debora Ribka Seknun, Fitri R. Seknun, M. F. Selangur, Djudid Sintje Sinay, L. J. Sinurat, Frisella Br Siska Siska Sjahruddin, Herman Sri Aulia Novita Sudirman Sudirman Syifa, Anisa Tamrin Tamrin Toumahuw, Imanuella Umbu Lapu, Ervan Suryanti Y. Matdoan, Muhammad Yunizar, Mahdayani Putri Zulnadi, Zulnadi