Check On-Time Performance of Domestic Airlines Using Random Forest Machine Learning Analysis

Ariyono Setiawan (), Efendi Efendi (), Ahmad Mubarok (), Kukuh Tri Prasetyo () and Untung Lestari Nur Wibowo ()
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Ariyono Setiawan: Akademi Penerbang Indonesia Banyuwangi.
Efendi Efendi: Akademi Penerbang Indonesia Banyuwangi.
Ahmad Mubarok: Akademi Penerbang Indonesia Banyuwangi.
Kukuh Tri Prasetyo: Akademi Penerbang Indonesia Banyuwangi.
Untung Lestari Nur Wibowo: Akademi Penerbang Indonesia Banyuwangi.

Technium Social Sciences Journal, 2023, vol. 43, issue 1, 570-583

Abstract: This study aims to analyze the On-Time Performance on domestic flights in Indonesia using the Random Forest machine learning analysis method. The purpose of this study is to predict On-Time Performance on domestic flights with high accuracy. The data used in this study are questionnaire data and factors that affect On-Time Performance on domestic flights in Indonesia. The results showed that the Random Forest model can produce On-Time Performance predictions on domestic flights with a high level of accuracy. Factors such as ground handling services, weather, and technical operations have a significant influence on On-Time Performance on domestic flights. The implication of this research is that it can help airlines optimize flight schedules and minimize flight delays, thus providing satisfaction to passengers

Keywords: On Time Performance; Machine Learning; Random Forest (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:tec:journl:v:43:y:2023:i:1:p:570-583

DOI: 10.47577/tssj.v43i1.8792

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