cover
Contact Name
Mohammad Amin Lasaiba
Contact Email
lasaiba.dr@gmail.com
Phone
+6285228918677
Journal Mail Official
amin.lasaiba@fkip.unpatti.ac.id
Editorial Address
Geography Education Program , Faculty of Teaching and Training Universitas Pattimura. Jl. Ir. M.Putuhena Poka Ambon
Location
Kota ambon,
Maluku
INDONESIA
GEOFORUM Jurnal Geografi dan Pendidikan Geografi
Published by Universitas Pattimura
ISSN : -     EISSN : 28306899     DOI : https://doi.org/10.30598/geoforumvol2iss1pp1-12
Core Subject : Science, Education,
Geography Education Physical Geography Human Geography Geographic Information System (GIS) Remote Sensing Environmental Science Disaster Mitigation
Articles 51 Documents
Sebaran Hujan Ekstrem dan Penerapan Prediksi IBFWS dalam Menilai Risiko Longsor di Kawasan Jazirah Leihitu Pulau Ambon Gina P. Batubara; Rafael M. Osok; Maimuna La Habi; Talakua, S.M
GEOFORUM 2026: Volume 5 Nomor 1
Publisher : Program Studi Pendidikan Geografi FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/geoforumvol5iss1pp26-39

Abstract

Landslides are a common hydrometeorological disaster in the Jazirah Leihitu region of Ambon Island, influenced by topographical conditions, rainfall intensity, and the area's vulnerability level. This study aims to analyze landslide risk levels, assess rainfall distribution patterns during landslide events, and evaluate the accuracy of the Impact-Based Forecast and Warning Services (IBFWS) system in predicting potential landslide impacts. The research methodology involves spatial mapping of hazard, vulnerability, and capacity, followed by spatial overlay with 24-hour rainfall data to produce IBFWS maps. Validation was conducted using a contingency table method. Results indicate that the majority of the area falls into the medium-risk category, while high-risk zones are scattered across western and central Leihitu Barat and the coastal region of Salahutu. IBFWS validation showed moderate accuracy for the July 8, 2022 event, with 66.67% accuracy and a skill score of 0.6667, but lower performance on August 24, 2022, with 33.33% accuracy and a skill score of 0.333. This study highlights the importance of strengthening impact-based early warning systems to enhance disaster mitigation and preparedness efforts in vulnerable areas.