Sistem Pendukung Keputusan Penentuan Lokasi Early Warning System Tanah Longsor Menggunakan TOPSIS
-
Aang Ma'ruf Perdana
*
Universitas Mercu Buana Yogyakarta, Yogyakarta,
Indonesia
- Mutaqin Akbar Universitas Mercu Buana Yogyakarta, Yogyakarta, Indonesia (*) Corresponding Author
Abstract
As one of the areas in the Special Region of Yogyakarta with a relatively high level of landslide vulnerability, Gunungkidul Regency requires targeted mitigation measures, including implementing an Early Warning System (EWS) to detect potential disasters early. The obstacle faced by the Gunungkidul Regency Regional Disaster Management Agency (BPBD) is the absence of a system that can support the process of determining priority locations for EWS installation objectively by considering various existing risk parameters. This research aims to develop a Decision Support System (DSS) by applying the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to produce priority recommendations for landslide EWS installation locations. The study utilized historical landslide occurrence data from BPBD Gunungkidul Regency covering the period of 2022–2025 and the Gunungkidul Regency Disaster Risk Assessment Document 2026–2030, with 116 villages (kalurahan) as the decision alternatives. The evaluation was conducted using four criteria: hazard, vulnerability, capacity, and landslide occurrence frequency. The results indicate that Sawahan Village achieved the highest preference value of 1.0000, followed by Mertelu Village with 0.9336 and Ngalang Village with 0.7481, making them the highest-priority locations for landslide EWS installation. The developed system successfully automates the TOPSIS calculation process, provides ranking results in a fast and transparent manner, and fulfills all functional requirements based on Black Box Testing. The proposed system is expected to support BPBD Gunungkidul Regency in determining priority locations for landslide Early Warning System (EWS) installation through a more measurable, data-driven, and objective decision-making process.
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