Forecasting Arrival Delay at Hartsfield–Jackson Atlanta International Airport ‎Using Autoregressive Fractionally Integrated Moving Average (ARFIMA)

Angga Pratama; Kiki Amelia; Gumgum Darmawan

doi:10.61579/future.v4i1.697

Authors

Angga Pratama Magister Statistika Terapan, Universitas Padjadjaran, Indonesia
Kiki Amelia Magister Statistika Terapan, Universitas Padjadjaran, Indonesia
Gumgum Darmawan Magister Statistika Terapan, Universitas Padjadjaran, Indonesia

DOI:

https://doi.org/10.61579/future.v4i1.697

Keywords:

ARFIMA, Keterlambatan Kedatangan, Peramalan Deret Waktu, Long-Memory, Efisiensi Operasional, Hartsfield–Jackson Atlanta Airport

Abstract

Keterlambatan penerbangan merupakan salah satu tantangan utama dalam menjaga efisiensi dan kualitas ‎layanan transportasi udara. Permasalahan ini berdampak pada peningkatan biaya operasional, gangguan ‎jadwal, serta penurunan kepuasan penumpang. Bandara Hartsfield–Jackson Atlanta International (ATL) ‎memiliki peran strategis sebagai pusat lalu lintas udara domestik di Amerika Serikat dengan volume ‎penerbangan tertinggi di dunia, sehingga memerlukan sistem peramalan yang akurat untuk mendukung ‎pengambilan keputusan operasional dan pengendalian lalu lintas udara. Penelitian ini bertujuan untuk ‎meramalkan keterlambatan kedatangan pesawat menggunakan model Autoregressive Fractionally ‎Integrated Moving Average (ARFIMA) yang mampu menangkap karakteristik long-memory pada data ‎deret waktu. Data yang digunakan berupa data bulanan keterlambatan kedatangan pesawat domestik ‎menuju ATL selama periode 2019–2023. Analisis dilakukan melalui tahapan identifikasi model, estimasi ‎parameter, diagnostik residual, serta evaluasi akurasi menggunakan ukuran Mean Absolute Scaled Error ‎‎(MASE). Hasil penelitian menunjukkan bahwa model terbaik adalah ARFIMA (1, d = 0,1821, 0) dengan ‎nilai MASE sebesar 0,876, yang menandakan tingkat akurasi peramalan yang baik. Model ini terbukti ‎efektif dalam menangkap pola fluktuasi jangka panjang dan ketergantungan temporal yang tidak dapat ‎dijelaskan oleh model ARIMA konvensional. Temuan ini menunjukkan bahwa pendekatan ARFIMA dapat ‎digunakan sebagai alat bantu dalam perencanaan operasional, pengelolaan kapasitas bandara, serta ‎pengendalian lalu lintas udara, khususnya untuk bandara besar seperti ATL yang memiliki tingkat ‎kepadatan penerbangan tinggi dan kompleksitas operasional yang besar.‎

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