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All Journal Gorga : Jurnal Seni Rupa JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Ampere The Indonesian Biomedical Journal Biomedical Journal of Indonesia Jurnal Pertanian Terpadu Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL PENDIDIKAN TAMBUSAI IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH SRIWIJAYA JOURNAL OF MEDICINE Psikostudia : Jurnal Psikologi Agroekoteknologi Tropika Lembab Poltekita : Jurnal Ilmu Kesehatan Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Ekonomi Bisnis Manajemen dan Akuntansi (EBMA) Community Empowerment IJISTECH Jurnal Pengabdian Masyarakat: Humanity and Medicine Hukum Responsif : Jurnal Ilmiah Fakultas Hukum Universitas Swadaya Gunung Jati Cirebon Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Elektro Jurnal Teknik Sipil Dinamis Digital Transformation Technology (Digitech) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Innovative: Journal Of Social Science Research Jurnal Pengmas Kestra (JPK) Local History & Heritage Jurnal Informatika Ekonomi Bisnis Jurnal Pustaka Dianmas Tarbiyah: Jurnal Ilmu Pendidikan dan Pengajaran Jurnal Indonesia Mengabdi (JIM) jle Journal of Technology and Computer (JOTECHCOM) PUBLIDIMAS Edukatif: Jurnal Pengabdian Masyarakat Economic Development Progress
Surya Darma
Program Studi Pendidikan Biologi FKIP Untan, Pontianak
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Journal : journal of technology and computer jotechcom

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Predictive Analysis of Flood Risk Factors Based on a Machine Learning Approach: Comparative Study of SVM and XGBoost Algorithms Darma, Surya; Al Fayed, Ahmad Jihad; P Pardede, Surya Maruli; Aqsha, Muhammad Hizbul; Novelan, Muhammad Syahputra
Journal of Technology and Computer Vol. 3 No. 1 (2026): February 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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Abstract

Flood events in Indonesia continue to increase in frequency and impact due to high rainfall variability, land-use change, and complex hydrological conditions. Accurate predictive modeling is therefore essential to support flood risk assessment and mitigation planning. This study evaluates the predictive performance of two supervised machine learning algorithms, Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost), for flood risk classification. The analysis is conducted using a publicly available dataset comprising 500 samples that represent multiple environmental and spatial factors related to flood occurrence. Data preprocessing includes cleaning, normalization, and feature consistency adjustment prior to model implementation. Both algorithms are trained and tested using the same dataset configuration to ensure objective comparison. Model performance is assessed using accuracy, precision, recall, and F1-score metrics. Experimental results indicate that XGBoost achieves higher accuracy and precision, demonstrating stronger capability in reducing false-positive predictions, while SVM shows relatively higher recall, reflecting better sensitivity in identifying flood-prone cases. Overall, XGBoost provides more reliable predictive performance for flood risk modeling on the dataset used. The findings confirm the effectiveness of machine learning-based approaches for flood risk prediction and highlight the importance of algorithm selection in disaster risk analysis.
Co-Authors . Apriansyah Abdullah, Ilmi Adinata, Triawan Al Fayed, Ahmad Jihad Alfathoni, Muhammad Ali Mursid Alferon, Hazalin Algifari, M. Ridho Novtriawan Al’amudi, Ivana Supi Angie, Evelyn Annisa Fithria Aqsha, Muhammad Hizbul Arikha Saputra Asrori, Muhamad Amin Asrullah Asrullah, Asrullah Azmi Ginting, Naufal Bagus Adi Nugroho Bahar Bahar, Bahar Bangun, Sri Melda Damanik, Abdi Rahim Desi, Efani Dewi Wahyuni Dhonanto, Donny Eddy Mart Salim, Eddy Mart Eka Irawan Elhias Nst, Mas Ayoe Ellanda Purwawijaya Fahrunsyah, Fahrunsyah Fayed, Ahmad Jihad Al Firzada, Fahmi fithry tahel, fithry Ginting, Erwin Ginting, Rosita Ginting, Subhan Hafiz Nanda Hadi Pranoto Harahap, Muhammad Farhan Harianto Harianto Helena, Shifa Hendri Budi Kurniyanto Hermansyah Hermansyah Hertanto, Rusdian Heru Satria Tambunan, Heru Satria Hidayat, Wahyu Handoyono Ibni Aura Sasabela Ibrahim Ibrahim Idris, Suria Darma Ikha Safitri Ilham Syahputra Saragih IMANG, NDAN Indra Gunawan Indrajaya, Taufik Indrawan, Yudhistira Fauzy Irmayani Irmayani John Juliandra, Obie Kasron Nst Khairul Amri Kriswiastiny, Rina KUNCORO, IWAN - kurniati, nova Kushadiwijayanto, Arie Antasari Kusumaningsih, Alvianita Rika Putri Liliana Puspa Sari Lubis, Yuliani Mardiati M. Rhifky Wayahdi Manesah, Dani MARIA BINTANG Matra, Ikahariya Pratiwi Mediarty, Mediarty Mega Sari Juane Sofiana Mikhael, Rodry Minsas, Sukal Monang, Sori Muhammad Amin Muhammad Reagan Muhammad Syahputra Novelan Muharraran, Firdha Mulya, Mhd. Ade Mulyadi Mulyadi Mulyadi, Asri Muthia, Putri Muthia, Putri Mutiar Mutiar, Mutiar Nefi Darmayanti Nora Idiawati Nur Riviati, Nur Nurdiansyah, Sy. Irwan Nurdiansyah, Syarif Irwan Nurhartanto, Nurhartanto Nurhasanah Nurhasanah Okprana, Harly P Pardede, Surya Maruli Panjaitan, Pranata Halasan Paranoan, Ria Rachel Pardede, Surya Maruli P Parinduri, Anggi Isnani Polem, Haga Putra Arza Prayitno, Dwi Imam Purnomo, Aji Putra, Dian Eka RACHMAT HIDAYAT Radiyati Umi Partan, Radiyati Umi Rahim Damanik, Abdi Rahman, Nopijal Rizki Ramadani, Alpin Ramadhan, Noor Muhammad Rizky Khairunnisa Sormin Rizqa Amelia, Rizqa Robiansyah, Wendi Roro Kesumaningwati Rudiyanto Rudiyanto, Rudiyanto ruziq, fahmi S, Budiman Salsabila, Ghaisani Samura, Jul Asdar Sarwoto Sarwoto, Sarwoto Silitonga, Aira Priamas Siti Aliyah Sri Wahyuni Sridewi, Nurmala Suherman, R.M. Edy Suherman, Suherman Sukma, Nimaz Tegar Sumarno . Syahputri, Aprilia Taufan Purwokusumaning Daru, Taufan Purwokusumaning Tia Nuraya Umi Partan, Radiyati Usman, Khairul Veithzal Rivai Zainal Warsidah, Warsidah Widodo Saputra Yulianto kusnadi Yuniza, Yuniza Yusuf Arief Nurrahman Zulkarnain Zulkarnain