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Journal : Journal of Applied Data Sciences

Machine Learning Models for Predicting Flood Events Using Weather Data: An Evaluation of Logistic Regression, LightGBM, and XGBoost Maharina, Maharina; Paryono, Tukino; Fauzi, Ahmad; Indra, Jamaludin; Sihabudin, Sihabudin; Harahap, Muhammad Khoiruddin; Rizki, Lutfi Trisandi
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.503

Abstract

This study examines flood prediction in Jakarta, Indonesia, a pressing concern due to its significant implications for public safety and urban management. Machine Learning (ML) presents promising methodologies for accurately forecasting floods by leveraging weather data. However, flood prediction in Jakarta remains challenging due to the city’s highly variable weather patterns, including fluctuations in rainfall, humidity, temperature, and wind characteristics. Existing methods often struggle with these complexities, as they rely on traditional ML models such as K-Nearest Neighbors (KNN), which may not capture certain patterns or provide high accuracy and robustness. Therefore, this study proposes three ML methods—Logistic Regression (LR), LightGBM, and XGBoost—to predict floods accurately. Five performance metrics (i.e., accuracy, area under the curve (AUC), precision, recall, and F1-score) were used to measure and compare the accuracy of the algorithms. The proposed method consists of three main processes. The first process involves data preprocessing and evaluation using 14 different ML models. In the second process, additional feature engineering is applied to improve the quality of the data. Finally, the third process combines the previous steps with oversampling techniques and cross-validation methods. This structured approach aims to enhance the overall performance of the analysis. The experimental results show that Process 3 significantly improves performance compared to Processes 1 and 2. The model predicts floods with an accuracy score of 93.82% for LR, 96.67% for XGBoost, and 96.81% for LightGBM, respectively. Thus, the proposed model offers a solution for operational decision-making in flood risk management, including flood mitigation planning.
Co-Authors AA Sudharmawan, AA Agustin, Siska Nur Ahmad Khusaeri Ahmad Yani, Asep Kuswara Ahmad, Aden Alfizzahra, Dinda Ainun Arimurti, Trias Atiqoh, Laili Ida Awaliya, Monica Ayu, Tirsa azzahra, rahma tiara Bima Satrio Husodo Della Sintya Rachman Devi Devi, Devi Dewi, Kurnia Dhiana Puspitawati Dwi Budi Santoso Eti Rusmalawati Fahmi rosyadi, Muhammad Faisal, Mochammad Aznawi falentino sembiring Fathul Laila, Fathul Fauji, Robby Fauji, Robby Fauji Firmansyah, Rahmadany Fitriyah, Ima Fuji, Robby Geni, Ariyanto Soewondo Hadani, Abdullah Hapsari, Puspita Ika Harjati, Eny Herman Suryokumoro Hidayat, Ahmad Wahyu Hidayaty, Dwi Epty Ijatna, Satia Bagdja Imas Marsipah, Siti Indra, Jamaludin Indrapura, Putri Fauziah Sri Ismawan, Almira Thalysa Jamaludin, Ludi Jannah, Reyhanatul Jauharoti Alfin Jeremia, Mario Ihutan Juhaeni Juhaeni Khoiriyah, Nadlifatul Lukita, Carolyn Luthfiyah, Rara Maharina, Maharina Mansur Mansur Mas'amah, Siti Mu'afifah, Amrissya Nurul Muhammad Khoiruddin Harahap Nanang Maulana Nida Fiya Umaini Nurwijayanti Otari, Widiati Hairina Pardana, I Nyoman Adi Paryono, Tukino Pasaribu, Erika Prasistanti, Aninda Rehani Rachman, Rino Arief Reka Dewantara RIKA KARTIKA Rizki, Lutfi Trisandi Rusmiati Rusmiati Sadat, Fahad Achmad Salsabila, Fadia Salsabila, Zuha Prisma Samudra, Hero Sandi, Santi Pertiwi Hari Savitri, Citra Shinta Hadiyantina Sholiha, Alfiatus Siti Hamidah Sudirman, M. Suhariningsih Sujaya, Fista Apriani Sukarmi Sukarmi, Sukarmi Sukarmi, Sukarmi Sundari, Putri Tria Surahman Surahman Titi Maryati Trisnawati Trisnawati Trisnayani, Larasati Tulandi, Edwin Steven Tulandi, Edwin Steven Ummah, Choiro Uswatun Chasanah Wahyuni, Dian Try Ananda Widia Lestari Winarno, Bambang Winarno, Bambang Yanti Yanti Yasep Setiakarnawijaya Zatinah, Rezi Zonyfar, Candra