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Abstract
The Bengkulu City area often experiences extreme weather with the potential for flooding and affects various types of human activities. This study aims to determine the effect of extreme weather predictor variables in Bengkulu City by using Statistical Product and Service Solutions (SPSS). Extreme weather indicators are reviewed based on rainfall with estimating variables in the form of air pressure, humidity, air temperature, and wind speed, for 5 years (2017-2021) obtained from the BMKG Station on Baai Island, Bengkulu City. Data processing using SPSS method. Data analysis was carried out statistically and descriptively. Based on the results of the study, the correlation between the estimator variables on extreme rainfall is quite good with r = 0.661, and the error value (RMSE) is 27,124. Furthermore, the homogeneity test between extreme rainfall indicators and extreme weather estimators includes air pressure, air temperature, wind speed, and air humidity, showing homogeneity in 2019. This indicates the predictor variable has the same direction to extreme rainfall, where the error value is obtained tends to be relatively small. The estimator variables, namely air pressure and humidity, have a significant relationship with extreme rainfall. Predictions using data (2017-2021) show that in 2022, extreme rainfall events will occur for a relatively long time, namely in January, March, May, June, July, August, October, and December. The most extreme rainfall intensity occurs in January
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Copyright (c) 2023 Mikael Simbolon, Supiyati, Suwarsono

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References
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References
Demski, C., Capstick, S., Pidgeon, N., Sposato, G. R. and Spence, A, “Experience Of Extreme Weather Affects Climate Change Mitigation And Adaptation Responses”, Jurnal Climatic Change, 140(2), pp 149–164, 2017.
Fadholi, A, “Persamaan Regresi Prediksi Curah Hujan Bulanan Menggunakan Data Suhu Dan Kelembaban Udara Di Ternate”, Jurnal Statistika, 13(1), pp 7–16, 2013.
Karmelina. Holiwarni, B. and Miharty, “Penerapan Model Pembelajaran Kooperatif Tipe TGT Menggunakan Chem Card Untuk Meningkatkan Prestasi Belajar Siswa Pada Pokok Bahasan Hidrokarbon Di Kelas X SMA Negeri 10 Pekanbaru”, pp6, 2014.
Nuraya, T., Ihwan, A. and Apriansyah, “Analisis Hujan Ekstrim Berdasarkan Parameter Angin Dan Uap Air Di Kototabang Sumatera Barat”, Jurnal Prisma Fisika, Program Studi Ilmu Kelautan Jurusan Fisika Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Tanjungpura, IV(01), pp 22–27, 2016.
Pradipta, S. N., Sembiring, P. and Bangun, P, “Analisis Pengaruh Curah Hujan Di Kota Medan”, Jurnal Saintia Matematika, 1(5), pp 459–468, 2013.
Putri, W. S. N. dan Suryati, K. N, “Modul Statistika Dengan SPSS”, Jurnal STIKI Indonesia, pp 1-4, 2016.
Sipayung, N. P. M, “Curah Hujan (Studi Kasus: Curah Hujan Periode 2001-2009 Pada Stasiun Dramaga)”, Skripsi, Program Studi Statistika Jurusan Statistika Fakultas Matematika Dan Ilmu Pengetahuan Alam Institut Pertanian Bogor, pp 1-18, 2012.
Surmaini, E., Runtunuwu, E. dan Las, I, “Upaya Sektor Pertanian Dalam Menghadapi Perubahan Iklim”, Jurnal Litbang Pertanian, 30(1), pp 1, 2011.
Yasin, H., Warsito, B. and Hakim, R. A, “Prediksi Curah Hujan Ekstrim Di Kota Semarang Menggunakan Spatial Extreme Value Dengan Pendekatan Max Stable Process (Msp)”, Jurnal Media Statistika, 12(1), pp 39, 2019.