Pemetaan Potensi Demam Berdarah Dengue Berbasis Weighted Overlay  di Kecamatan Rejoso, Kabupaten Nganjuk

Muhammad Luqmanul Hakim; Yushardi Yushardi; Muhammad Asyroful Mujib; Sri Astutik; Ana Susiati

doi:10.22146/mgi.109618

Pemetaan Potensi Demam Berdarah Dengue Berbasis Weighted Overlay di Kecamatan Rejoso, Kabupaten Nganjuk

https://doi.org/10.22146/mgi.109618

Muhammad Luqmanul Hakim⁽¹⁾, Yushardi Yushardi^(2*), Muhammad Asyroful Mujib⁽³⁾, Sri Astutik⁽⁴⁾, Ana Susiati⁽⁵⁾

(1) Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jember, Jember, Indonesia
(2) Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jember, Jember, Indonesia
(3) Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jember, Jember, Indonesia
(4) Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jember, Jember, Indonesia
(5) Program Studi Pendidikan Geografi, Fakultas Keguruan dan Ilmu Pendidikan, Universitas Jember, Jember, Indonesia
(*) Corresponding Author

Abstract

Abstrak. Kecamatan Rejoso, Kabupaten Nganjuk mengalami peningkatan signifikan kasus Demam Berdarah Dengue (DBD) dari 10 kasus pada Tahun 2023 menjadi 57 kasus pada Tahun 2024. Kenaikan kasus DBD ini diduga berkaitan dengan faktor lingkungan seperti curah hujan, kelembapan udara, suhu. Indeks kerapatan vegetasi, dan indeks kebasahan. Pemetaan spasial berbasis data citra satelit dan sistem informasi geografis telah banyak digunakan dalam studi epidemiologi, namun demikian penerapannya masih terbatas dalam konteks lokal dengan pendekatan kuantitatif berbasis fisiografi wilayah dan indeks spektral. Penelitian ini bertujuan untuk memetakan potensi risiko DBD menggunakan pendekatan weighted overlay berbasis Principal Component Analysis (PCA). Penelitian ini bersifat deskriptif kuantitatif, dengan data diperoleh melalui studi pustaka, observasi, dokumentasi, serta analisis citra satelit. Hasil PCA menunjukkan variabel paling berpengaruh adalah curah hujan (0,530), kelembapan udara (0,509) dan kerapatan vegetasi (0,421), sedangkan suhu (-0,509) dan indeks kebasahan (0,148) memberikan kontribusi yang lebih rendah. Pemetaan menunjukkan tiga kategori potensi DBD, yaitu tinggi (6 desa), sedang (4 desa), dan rendah (13 desa). Temuan ini memperlihatkan bahwa weighted overlay dapat digunakan sebagai alat prediksi spasial untuk mendukung mitigasi risiko dan kewaspadaan dini terhadap DBD, dengan mempertimbangkan dinamika iklim lokal dan karakteristik lingkungan wilayah.

Abstract. The Rejoso District in Nganjuk Regency experienced a significant increase in Dengue Hemorrhagic Fever (DHF) cases, rising from 10 cases in 2023 to 57 cases in 2024. This increase in DHF cases is thought to be related to environmental factors such as rainfall, air humidity, temperature, vegetation density index, and wetness index. Spatial mapping based on satellite imagery data and Geographic Information Systems has been widely used in epidemiological studies, but its application is still limited in the local context, with a quantitative approach based on regional physiography and spectral index. This study aims to map the potential risk of DHF using a weighted overlay approach based on Principal Component Analysis (PCA). This study is a descriptive, quantitative research, with data collected through literature reviews, observations, documentation, and satellite image analysis. PCA results show that the most influential variables are rainfall (0.530), air humidity (0.509) and vegetation density (0.421), while temperature (-0.509) and wetness index (0.148) provide a lower contribution. The mapping revealed three categories of dengue fever potential: high (in 6 villages), medium (in 4 villages), and low (in 13 villages). These findings demonstrate that weighted overlay can be used as a spatial prediction tool to support risk mitigation and early warning of dengue fever, taking into account local climate dynamics and the region's environmental characteristics.

Keywords

Demam Berdarah Dengue; Pemetaan; Principal Component Analysis; Weighted Overlay.

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DOI: https://doi.org/10.22146/mgi.109618