Sakinah, Nita Inas (2017) Measuring mental workload of air traffic controller (ATC) by using dynamic density (DD) and nasa-tlx methods (case study: airnav Indonesia Surabaya branch office). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Today’s growth of Juanda Airport air transport service is very rapid. To ensure the service quality and safety, one of most significance aspects is relied on ATC performance under AirNav Juanda management. This performance depends on appropriate workload burdened towards the ATC. Therefore, an ATC workload measurement is important to be conducted. Especially for Approach Unit (APP) Controller who has so many cognitive tasks. The tasks are prevent collision between aircrafts, expedite and maintain an orderly of air traffic flow, provide advice and information for the safe and efficient flight, and notify relevant organizations regarding aircraft in need of rescue and assist the mentioned organization if it is required. Moreover, this unit does not only handle departing and arriving flights, but also the passing through flights through its sectors.
One of objective methods which represent cognitive complexity factors that mainly trigger APP Controller mental workload is Dynamic Density (DD). In the application towards AirNav Juanda, DD is supported by a widely used subjective method, NASA-TLX. It is because there is still no objective mental workload which able to precisely represent the ATC level of workload.
Result of AirNav Juanda APP Controller mental workload triggering factors measurement by using DD shows top 5 weighting of the factors are S5, NUMHORIZ, SCI, SV and C15 respectively. Moreover, based on NASA-TLX assessment, 9.1% of 22 observed APP Controllers experience ‘very high’ category of mental workload, 81.8% ‘high’ and 9.1% ‘medium high’. This workload is triggered by the complexity factors as measured by DD with result of R2 for 0.60497.
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Dewasa ini, permintaan pelayanan transportasi udara di Bandara Juanda
bertumbuh sangat pesat. Untuk memastikan kualitas dan keamanan layanannya,
salah satu aspek yang paling penting adalah kinerja Air Traffic Controller (ATC)
di bawah manajemen AirNav Juanda. Kinerja tersebut bergantung pada
keseimbangan beban kerja yang ATC rasakan. Oleh karenanya, pengukuran beban
kerja ATC merupakan hal yang penting untuk dilakukan. Terutama untuk
Approach Unit (APP) Controller yang memiliki banyak tuntutan tugas kognitif.
Tugas tersebut antara lain mencegah tabrakan antar pesawat, melancarkan dan
menjaga keteraturan arus lalu lintas udara, menyediakan saran serta informasi
untuk penerbangan yang aman dan efisien, dan mengabari organisasi terkait
pertolongan pada pesawat serta mendampinginya apabila dibutuhkan. Unit ini
tidak hanya menangani pesawat yang menuju atau meninggalkan Bandara Juanda,
namun juga pesawat yang melintas di sektor-sektor udaranya.
Salah satu metode objektif yang dapat merepresentasikan faktor kerumitan
kognitif sebagai pemicu utama beban kerja mental APP Controller adalah
Dynamic Density (DD). Dalam pengaplikasiannya di AirNav Juanda, DD
didukung oleh sebuah metode subjektif yang telah banyak dipakai, yaitu NASATLX. Hal ini karena belum adanya metode pengukuran beban kerja mental secara
objektif yang benar-benar mampu merepresentasikan beban kerja tersebut.
Hasil pengukuran faktor-faktor pemicu beban kerja mental APP Controller
AirNav Juanda menggunakan DD didapatkan urutan 5 faktor kompleksitas lalu
lintas udara tertinggi yaitu S5, NUMHORIZ, SCI, SV, dan disusul dengan C15.
Kemudian berdasar pengukuran NASA-TLX, APP Controller yang merasa beban
kerjanya „sangat tinggi‟ ada 9.1%, „tinggi‟ sebanyak 81.8%, dan „menengah
tinggi‟ sejumlah 9.1% dari 22 responden. Beban kerja tersebut dipicu oleh faktorfaktor kerumitan sebagaimana yang telah diukur menggunakan DD dengan R2
sekitar 0.60497.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Workload, Dynamic Density, NASA-TLX, ATC, AirNav Juanda |
| Subjects: | H Social Sciences > HE Transportation and Communications > HE355 Traffic engineering |
| Divisions: | Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | Nita Inas Sakinah |
| Date Deposited: | 06 Oct 2017 03:39 |
| Last Modified: | 08 Mar 2019 02:48 |
| URI: | http://repository.its.ac.id/id/eprint/45798 |
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