Karakteristik Angin dan Risiko Operasional Runway di Bandara Soekarno-Hatta pada Bulan Basah (DJF)

Abstract

Penelitian ini bertujuan untuk menganalisis dinamika karakteristik komponen angin (headwind, tailwind, dan crosswind) di Bandara Internasional Soekarno-Hatta pada musim basah (DJF) tahun 2020–2024 menggunakan data Aerodrome Climate Summary (ACS). Analisis awal dilakukan melalui visualisasi Windrose dan dekomposisi vektor untuk memperoleh distribusi spasial-temporal komponen angin (headwind, tailwind, dan crosswind). Regresi logistik multinomial digunakan untuk mengkuantifikasi hubungan antara parameter meteorologis dan peluang terjadinya empat kategori insiden di runway: Cancel Approach, Go Around, Veer Off, dan Hard Landing. Hasil analisis Windrose menunjukkan bahwa dominasi arah angin dari barat hingga barat laut, dengan kecepatan rata-rata 1,94–9,72 knot, yang berimplikasi pada kecenderungan headwind terhadap runway 07L. Dekomposisi Vektor tailwind merupakan komponen angin yang paling sering terjadi, disusul oleh crosswind kiri dan crosswind kanan. Headwind merupakan komponen dengan frekuensi paling rendah. Temuan ini sejalan dengan studi yang menyoroti pentingnya karakteristik angin dalam mendukung keselamatan operasi bandara. Selanjutnya hasil regresi logistik multinomial menunjukkan bahwa model terbaik diperoleh dengan variabel X3 dalam bentuk kontinu, menghasilkan pseudo R-square sebesar 93% dan akurasi klasifikasi sebesar 75,4%. Ditemukan bahwa risiko Cancel Approach (batal mendarat sebelum menyentuh landasan) dan Hard Landing (pendaratan menghantam landasan terlalu keras) lebih dipengaruhi oleh tailwind dan kecepatan angin tinggi, sedangkan Go Around (batal mendarat di fase akhir, pesawat naik lagi) dan Veer Off (pesawat keluar dari jalur runway) lebih dipicu oleh crosswind dan kecepatan angin tinggi. Jenis pesawat juga berpengaruh signifikan, dimana pesawat kecil lebih rentan terhadap semua kategori insiden di landasan pacu dibandingkan pesawat besar. Pendekatan serupa dalam pemodelan insiden runway dan klasifikasi kerusakan pesawat telah terbukti efektif dalam penelitian terdahulu yang menyoroti peran signifikan kecepatan dan arah angin dalam insiden penerbangan.

This study aims to analyze the dynamics of wind component characteristics (headwind, tailwind, and crosswind) at Soekarno-Hatta International Airport during the wet season (DJF) from 2020 to 2024 using Aerodrome Climate Summary (ACS) data. The initial analysis was conducted through Windrose visualization and vector decomposition to obtain the spatio-temporal distribution of wind components (headwind, tailwind, and crosswind). Multinomial logistic regression was then applied to quantify the relationship between meteorological parameters and the probability of four categories of runway incidents: Cancel Approach, Go Around, Veer Off, and Hard Landing. The Windrose analysis revealed that wind direction was predominantly from the west to northwest, with an average speed of 1.94–9.72 knots, implying a tendency toward headwind conditions on runway 07L. Vector decomposition further showed that tailwind was the most frequently occurring wind component, followed by left and right crosswinds, while headwind occurred with the lowest frequency. These findings are consistent with previous studies emphasizing the critical role of wind characteristics in supporting airport operational safety. Furthermore, the results of the multinomial logistic regression indicated that the best-fit model was obtained when wind speed (X3) was treated as a continuous variable, yielding a pseudo R-square of 93% and a classification accuracy of 75.4%. The analysis revealed that the risks of Cancel Approach (aborted landing before touchdown) and Hard Landing (excessively forceful touchdown) were primarily influenced by tailwind and high wind speed, whereas Go Around (aborted landing at the final phase, aircraft climbing again) and Veer Off (aircraft veering off the runway) were more strongly triggered by crosswind and high wind speed. Aircraft type also had a significant effect, with smaller aircraft being more vulnerable to all categories of runway incidents compared to larger aircraft. A similar modeling approach in runway incident analysis and aircraft damage classification has been proven effective in previous studies, highlighting the significant role of wind speed and direction in flight-related incidents.