Behavioral evidence of public aircraft with historical data: The case of Boeing 737 MAX 8 PK-LQP

Passarella, Rossi; Nurmaini, Siti

doi:10.5937/jaes0-38696

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…(1), while precision is a formula to determine the ratio of data that is predicted positive to the overall data, as seen in Eq. (2). Next is referred to as "recall."…”

Section: Actual Classificationmentioning

confidence: 99%

“…The three main causes of aviation accidents during takeoff and landing-technical issues, weather, and human error-generally account for 63% of all accidents involving aircraft [1]. Accident analysis during the take-off or landing phase now depends solely on data from the black box, whereas, as information technology advances, data from the Automatic Dependent Surveillance-Broadcast (ADS-B) should be a concern in order to see alternative points of view in the accident analysis process [2]. Yet, the ADS-B signal quality is the most important component in convincing the analytical results utilizing ADS-B data.…”

Section: Introductionmentioning

confidence: 99%

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Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm

Yousnaidi,

Passarella,

Kurniati

et al. 2023

MITS

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This study aims to assess the safety level of the Automatic Dependent Surveillance-Broadcast (ADS-B) signal quality during airplane departures at Sultan Mahmud Badaruddin II Airport. The Aero-track application was utilized to monitor commercial aircraft departures and collect observation data. The collected data underwent processing using data analysis algorithms and labeling processes, resulting in a comprehensive dataset for evaluating ADS-B signal quality. Signal quality was categorized into four levels, and a model was built using the Random Forest algorithm, achieving an accuracy of 99%. Comparative analysis with SVM and Naive Bayes algorithms showed accuracy values of 93% and 97% respectively. Consequently, the Random Forest Model was chosen for estimating ADS-B signal quality during commercial aircraft takeoff and landing.

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“…(1), while precision is a formula to determine the ratio of data that is predicted positive to the overall data, as seen in Eq. (2). Next is referred to as "recall."…”

Section: Actual Classificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm

Yousnaidi,

Passarella,

Kurniati

et al. 2023

MITS

View full text Add to dashboard Cite

show abstract

“…The initial phase involved delineating the analysis' purpose. By defining the objective of the data analysis, appropriate variables can be selected to facilitate conclusion drawing and hypothesis or research question testing [15]. The intention of this study was to scrutinize the ICAO's impact on aviation safety, accomplished by examining fluctuations in accident count, fatalities, and material losses over time.…”

Section: Figure 1 Stages Of Studymentioning

confidence: 99%

Evaluating the Influence of the International Civil Aviation Organization on Aircraft Accident Rates and Fatalities: A Seven-Decade Historical Data Analysis

Passarella,

Veny,

Fachrurrozi

et al. 2023

ATAMS

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The advent of air travel, originally proposed by the Wright brothers, has led to a significant surge in aircraft usage for human transportation. In its nascent stages, this mode of transport was linked with a high frequency of accidents and consequent fatalities, placing it in the high-risk category. To counter these risks, the International Civil Aviation Organization (ICAO) was established in 1947 as a collaborative effort among numerous countries with the primary goal of enhancing aviation safety regulations. This study analyzed archival data from the Bureau of Aircraft Accidents Archives (B3A), covering a span of 72 years from 1918, the year of the first commercial airplane crash, until 2020. The objective was to understand the ICAO's impact on altering accident rates, fatalities, and underlying causes. Analytical methodologies encompassed both descriptive statistics-examining data distribution, central tendencies, and category frequencies-and exploratory data analysis (EDA) to identify variable relationships and outlier identification. The results indicated that ICAO's interventions have led to a notable decline in accident rates, with an annual average reduction of 70.9%, and a corresponding decrease in incidents attributed to technical factors. However, an unexpected trend was the increase in fatalities despite the drop in accident numbers, attributable to the introduction of larger aircraft designs carrying more passengers per flight. The findings underscore the ICAO's successful efforts in reducing aircraft accidents, but also suggest a need for further exploration into factors contributing to the rise in fatalities.

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Development of a machine learning model for predicting abnormalities of commercial airplanes

Passarella,

Nurmaini,

Rachmatullah

et al. 2024

Data Science and Management

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Behavioral evidence of public aircraft with historical data: The case of Boeing 737 MAX 8 PK-LQP

Cited by 4 publications

References 19 publications

Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm

Assessing Automatic Dependent Surveillance-Broadcast Signal Quality for Airplane Departure Using Random Forest Algorithm

Evaluating the Influence of the International Civil Aviation Organization on Aircraft Accident Rates and Fatalities: A Seven-Decade Historical Data Analysis

Development of a machine learning model for predicting abnormalities of commercial airplanes

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