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All Journal Jurnal Ilmu Dasar Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Jurnal Neutrino : jurnal fisika dan aplikasinya JGE (Jurnal Geofisika Eksplorasi) Jurnal Inovasi dan Pembelajaran Fisika Jurnal Sains Teknologi dan Lingkungan (JSTL) Jurnal Penelitian Pendidikan IPA (JPPIPA) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Pengabdian Magister Pendidikan IPA Jurnal Fisika : Fisika Sains dan Aplikasinya Indonesian Physical Review Kappa Journal Lensa : Jurnal Kependidikan Fisika Jurnal Penelitian dan Pembelajaran Fisika Indonesia Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Lensa: Jurnal Kependidikan Fisika Indonesian Journal of Physics (IJP) Dharma Pengabdian Perguruan Tinggi (DEPATI) Jurnal Pertambangan dan Lingkungan Alamtana Asskruie Frontier Advances in Applied Science and Engineering Media for Empowerment, Mobilization, and Innovation in Research & Community
Suhayat Minardi
Program Studi Fisika, FMIPA, Universitas Mataram, Mataram, Indonesia
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Journal : Frontier Advances in Applied Science and Engineering

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Monthly Rainfall Prediction Using Multiple Linear Regression Method in West Nusa Tenggara Region Minardi, Suhayat; Baihaqi, Anas; Wazni, Haerul
Frontier Advances in Applied Science and Engineering Vol. 3 No. 1 (2025)
Publisher : Tinta Emas Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59535/faase.v3i1.456

Abstract

Rainfall is a crucial meteorological element in tropical regions like Indonesia. The significant influence of rainfall on various sectors of life means that rainfall predictions are necessary for making plans. This research aims to determine the accuracy of rainfall predictions using the Multiple Linear Regression method and what local factors influence rainfall in the West Nusa Tenggara Region. Multiple Linear Regression is a method that can predict monthly rainfall using more than one independent variable. There are inconsistencies in the regression analysis process, and to overcome this in this study, DMC (Double Mass Curve) was used. The data used is BMKG data from the West Nusa Tenggara (NTB) Climatology Station for 2013 - 2022. In general, the level of prediction accuracy ranges between 54.10% - 87.50%. The best correlation coefficient value for the Lombok Island Region is r = 0.79. The Sumbawa Island region is r = 0.88, and the Bima region is r = 0.83. Based on the multiple linear regression equation model obtained, the most dominant local factors influencing rainfall in the NTB region are air and sea surface temperatures.
Co-Authors Adella Ulyandana Jayarti Adella Ulyandana Jayatri Adi Susilo Agus Naba Agus Wahid Ahmad Mudyanto Ahmad Rifaldi Arahman Akhmad Solikhin Al Fatari, Hotinul Al Hadi, Kasnawi Alaa, Siti Alfina Taurida Alaidrus Alfina Taurida Alaydrus Alhadi, Kasnawi Aminy, Ika Umratul Asni Aprianti, Nirmala Arif Budianto Arif Budiarto Ayu Mona Erisa Marpaung Baihaqi, Anas Bakti Sukrisna Bakti Sukrisna Bambang Sunardi, Bambang Budianto, Ari Daharta Dahrin Deni Hermansyah Dian Wijaya Kurniawidi Dieni Haryati Utami Elinda, Baiq Ulfa Putri Fidya, Karina Alma Handayana, I Gusti Ngurah Yudi Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden Hiden I Wayan Sudiarta Ika Umratul Asni Aminy Inayah, Rahmatun Indra Arifianto Istiqomah, Melinda Utami Izyatin, Nazla Jayatri, Adella Ulyandana Kasnawi Al Hadi Kormil Saputra Laela Zulfawati Laili Mardiana Lalu Sahrul Hudha Lestari, Vista Ayu Lily Syahana Rahim Mahmud Yusuf Marzuki Marzuki Marzuki Marzuki Muh Sarkowi Muhammad Amin Muhammad Jarul Rozki Nela Ranita Amanda Nurul Qomariyah NURUL QOMARIYAH Nurul Qomariyah Nurul Qomariyah Pratama, Muhammad Andika Rahadi Wirawan Rahmatullah, Ovan Rahmatun Inayah Ramadian Ridho Illahi Rima Yudiana Satriawan Satriawan, Satriawan Siti Alaa’ Siti Azizah Sri Rizki Eka Putri Sukrisna, Bakti Susi Rahayu Syamsuddin Syamsuddin Syamsuddin Syamsuddin Syamsuddin Teguh Ardianto, Teguh Teguh Rifandi Wardani, Aulia Fatma Wazni, Haerul Wibowo, Rahmat Catur Wijaya, Roviq Wirawan, Rahadi Zulfatiha, Septhia Salwa Zulfawati, Laela Zyiadatun Adawiah