Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing

Pratiwi, Winda; Sofwan, Aghus; Setiawan, Iwan

doi:10.11591/ijai.v10.i3.pp545-552

Akses terbuka Jurnal SINTA 1

Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing

IAES International Journal of Artificial Intelligence · Vol. 10 No. 3 (2021) · hlm. 545–552

DOI: 10.11591/ijai.v10.i3.pp545-552
ISSN: 2252-8938, 2089-4872
Terbit: 2021-09-01
Penerbit: Institute of Advanced Engineering and Science
Bahasa: eng
Lisensi: creativecommons.org/licenses/by-sa/4.0

Abstrak

In the landing process, airplanes have many safety factors that must be protected. Weather advice and information is very important as a consideration in determining the feasibility of landing an aircraft. The main objective of this research is the implementation of Mamdani fuzzy simulation in determining the feasibility of landing aircraft at Ahmad Yani Airport in Semarang using ATC police and pilot coordination on runway number 31. Wind direction, wind velocity, visibility, and pilot experience are used to determine eligibility aircraft landing. An intelligent system based on fuzzy logic produces three decisions that are feasible, careful, and not feasible in landing an aircraft on a runway. The results of the study concluded from an intelligent system based on fuzzy logic can be used to determine aircraft landing decisions on the runway of Ahmad Yani Airport Semarang on runway number 31.

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15 penulis · 26 tautan kepenulisan bersama · 7 lintas organisasi

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Diponegoro University
Sultan Agung Islamic University
State University of Semarang
Lampung University
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Organisasi sama
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Tampilkan sebagai tabel

Rekan penulis	Organisasi	Artikel bersama
Abdul Syakur	Diponegoro University	3
Teguh Budi Prakoso	Diponegoro University	1
Eko Arifianto	Diponegoro University	1
Arief Marwanto	Sultan Agung Islamic University	1
Sukarno Budi Utomo	Diponegoro University	1
Berkah Fajar	Diponegoro University	1
Sonny Hady Winoto	Afiliasi tidak diketahui	1
Yudha Agung Subarkah	Diponegoro University	1
Teuku Khairul Murad	Diponegoro University	1
Rahmat Gernowo	Diponegoro University	1
Basworo Ardi Pramono	State University of Semarang	1
Luthfiyyatun Mardiyah	Lampung University	1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.

Metadata asli (oai_dc)

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	<dc:title xml:lang="en-US">Implementation of fuzzy logic method for automation of decision making of Boeing aircraft landing</dc:title>
	<dc:creator>Pratiwi, Winda</dc:creator>
	<dc:creator>Sofwan, Aghus</dc:creator>
	<dc:creator>Setiawan, Iwan</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">Aircraft; Fuzzy logic Mamdani; Landing; Pilot experience; Weather</dc:subject>
	<dc:description xml:lang="en-US">In the landing process, airplanes have many safety factors that must be protected. Weather advice and information is very important as a consideration in determining the feasibility of landing an aircraft. The main objective of this research is the implementation of Mamdani fuzzy simulation in determining the feasibility of landing aircraft at Ahmad Yani Airport in Semarang using ATC police and pilot coordination on runway number 31. Wind direction, wind velocity, visibility, and pilot experience are used to determine eligibility aircraft landing. An intelligent system based on fuzzy logic produces three decisions that are feasible, careful, and not feasible in landing an aircraft on a runway. The results of the study concluded from an intelligent system based on fuzzy logic can be used to determine aircraft landing decisions on the runway of Ahmad Yani Airport Semarang on runway number 31.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2021-09-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/20873</dc:identifier>
	<dc:identifier>10.11591/ijai.v10.i3.pp545-552</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 10, No 3: September 2021; 545-552</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v10.i3</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/20873/13200</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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