ABSTRAK Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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COVER Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB1 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB2 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB3 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB4 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB5 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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BAB6 Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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PUSTAKA Vatresya Vanya Rivensy
Terbatas  Irwan Sofiyan
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Terbatas  Irwan Sofiyan
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At the core of every air transportation system lies a complex network of airports
collectively known as the air transportation network (ATN). Within this system, the
active exchange of flights between various airport origins and destinations forms a
network of routes. These routes can be enriched with essential details, including
how often flights happen, how many passengers they carry, and more. This
fundamental structure becomes even more important when considering the crucial
role of the air transport network (ATN) in enabling the movement of people and
goods within a country. This significance is particularly notable in countries like
Indonesia, characterized by numerous islands where efficient connections become
a foundation for smooth mobility.
Considering the significance of the air transportation network (ATN) in Indonesia,
an in-depth analysis of Indonesian airport connectivity is crucial to understanding
its topology structure and characteristics. This includes understanding the
connections between various regional and hub airports, identifying key airport hubs
within multiple regions in Indonesia, and exploring other aspects. The analysis in
this study will be achieved through a complex network approach followed by the
calculation using network topology metrics, including the metrics for nodes’
centrality, network structure, and the correlation between the metrics.
The Indonesian Air Transport Network (IATN) analysis unveils characteristics of
a small-world network, evidenced by an average path length of 3 and a clustering
coefficient of 0.484, which align with patterns observed in other countries’ air
transportation networks. The analysis also reveals that the network's cumulative
degree distribution adheres to a truncated-power law function, indicating the
presence of hubs, akin to the scenario in India. Moreover, the IATN follows a
disassortative mixing pattern in its degree correlation, distinguishing it from the
Worldwide Airport Network (WAN) while drawing parallels with the airport
networks of China, India, and Australia.