Prediksi Kerentanan Kekeringan Perkotaan Menggunakan Machine Learning: Pendekatan untuk Perencanaan Kota Tangguh di Kota Kupang

Authors

  • Eglantyne Lidya Subnafeu Program Studi Perencanaan Wilayah dan Kota, ITN Malang
  • Mohammad Reza Program Studi Perencanaan Wilayah dan Kota, Institut Teknologi Nasional Malang
  • Ardiyanto Maksimilianus Gai Program Studi Perencanaan Wilayah dan Kota, Institut Teknologi Nasional Malang
  • Firman Afrianto Ikatan Ahli Perencanaan Jawa Timur https://orcid.org/0000-0002-9369-8713

DOI:

https://doi.org/10.32493/jtsi.v8i2.43780

Keywords:

NDDI, Kerentanan Kekeringan, Machine Learning, Kota Tangguh

Abstract

The city of Kupang in East Nusa Tenggara faces increasingly serious drought challenges due to climate change and rapid urbanization, prompting the need for this study to predict drought vulnerability in the region. This study aims to develop a drought vulnerability prediction model using a machine learning approach that combines Normalized Difference Drought Index (NDDI) data, built-up areas, and population data in the last five (5) years. The methods used include NDDI calculations from satellite imagery, a zonal statistical analysis, and drought vulnerability simulations using models such as Random Forest, Support Vector Machine, and Artificial Neural Network. The results show that the Random Forest model provides the best prediction with the highest R Squared value, and indicates an increased risk of drought in several villages in 2030 and 2040, especially in areas with rapid population growth and expansion of built-up areas. The conclusion of this study confirms that the developed approach is able to provide a more accurate picture of drought-prone areas, so that it can be an important guide in more resilient and sustainable urban  planning, and recommends strengthening water management and spatial planning policies with early intervention in the most vulnerable areas.

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Published

2025-04-30

How to Cite

Subnafeu, E. L., Reza, M., Gai, A. M., & Afrianto, F. (2025). Prediksi Kerentanan Kekeringan Perkotaan Menggunakan Machine Learning: Pendekatan untuk Perencanaan Kota Tangguh di Kota Kupang. Jurnal Teknologi Sistem Informasi Dan Aplikasi, 8(2), 69–82. https://doi.org/10.32493/jtsi.v8i2.43780

Issue

Vol. 8 No. 2 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi

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Article

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Copyright (c) 2025 Eglantyne Lidya Subnafeu, Mohammad Reza, Ardiyanto Maksimilianus Gai, Firman Afrianto

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