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Abstrak :
Penelitian ini membahas permasalahan strategi peningkatan kinerja lalu lintas di ruas Jl. P2 akibat bangkitan lalu lintas yang terjadi di tahun 2017 sebagai dampak dari pengoperasian Terminal 3 Ultimate Bandara Soekarno-Hatta. Analisis didasarkan atas perhitungan kinerja lalu lintas eksisting yang mengacu kepada Dirjen Bina Marga 1997, membuat model jaringan lalu lintas eksisting, menghitung forecast volume lalu lintas berdasarkan pertumbuhan jumlah penumpang yang telah di validasi, serta uji skenario permodelan lalu lintas Do Nothing dan Do Something menggunakan perangkat lunak Vissim. Hasil analisis berdasarkan skenario Do Something menunjukkan penurunan arus lalu lintas sebesar 21.57 dari total arus lalu lintas di ruas Jalan P2 dan dibuktikan dengan peningkatan kinerja lalu lintas rata-rata sebesar 13.64 untuk kecepatan, 65.02 untuk tundaan, serta 0.93 untuk panjang antrian lalu lintas dibandingkan dengan hasil skenario Do Nothing. Hasil penelitian ini berupa peningkatan kinerja lalu lintas pada Jl. P2 dan Simpang Perimeter Utara setelah dilakukan penguraian arus lalu lintas melalui jalur alternatif khusus karyawan. ......The aim of this research is to develop a strategy that improves the traffic performance at P2 lane due to the prediction of increased traffic in 2017 as the impact of the operation of Terminal 3 Ultimate Soekarno Hatta Airport. Analysis are based on existing traffic performance calculation that refer to Dirjen Bina Marga 1997 , designing an existing traffic network model, calculation of the volume of traffic forecast based on growth in the number of passengers that have been validated, and testing the traffic model with the Do Nothing and Do Something scenario using Vissim software. The analysis indicates that for Do Something scenario, traffic flow potentially decreases up to 21.57 and proven by an increase in traffic performance of 13.64 for speed, 65.02 for queue delay, and 0.93 for traffic queue length compared with the result of Do Nothing scenario. The result of this research, consisting the increasing traffic performance on P2 lane and Simpang Perimeter Utara after splitting the traffic flow through the special alternative route for employee is based on the result of traffic modeling using Vissim software. Keywords trip production, model, splitting the traffic flow, special alternative route.

Abstrak :
ABSTRAK
Penelitian ini dimaksudkan untuk mengetahui berapa besar pengaruh penambahan taxiway penghubung sisi timur dalam mengoptimalkan kapasitas bandar udara Soekarno Hatta. Observasi dilakukan untuk melihat waktu tempuh yang dipergunakan untuk mencapai parkir (apron) dari runway dari posisi mendarat di Bandara Soekarno Hatta. Metode yang dilakukan adalah melakukan pengamatan secara langsung terhadap pergerakan pesawat yang mendarat di runway utara yang parkir di terminal utara dan selatan, pergerakan pesawat yang mendarat di runway selatan yang parkir di terminal utara dan selatan. Pengolahan data dilakukan dengan cara uji korelasi, dan analisa jaringan. Hasil analisa diperoleh waktu tempuh pada taxiway penghubung sisi timur adalah 132,02 + t detik, dengan t adalah koefisien waktu tempuh akibat posisi pendaratan. Akibat penambahan taxiway penghubung sisi timur mengakibatkan penambahan kapasitas landas pacu sebesar 31 % dan pengurangan delay sebesar 0,56 %.

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ABSTRACT
This study is intended to determine how large the effect of adding taxiways connecting the east side in order to optimize the capacity of Soekarno Hatta airport. Observation was done to see the travel time used to parking at apron of the position of the landing runway at Soekarno Hatta Airport. The method used is to conduct direct observation of the movement of the plane landed on the runway north terminal parking at the north and south, and observation the movement of aircraft that landed in the parking lot south runway at the north and south terminals. Data processing is done by testing the correlation, and network analysis. Travel time analysis results obtained on the taxiway connecting the east side is 132.02 + t seconds, where t is the travel time coefficient due to the landing position. Due to the addition of taxiway connecting the east side of the runway resulting in additional capacity by 31% and 0,56 % delay reduction

Abstrak :
Pertumbuhan industri penerbangan telah mendorong peningkatan permasalahan runway allocation dan gate assignment di bandara. Permasalahan tersebut mendorong terjadinya permasalahan kelebihan kapasitas dan akan sangat berpengaruh pada tingkat pelayanan bandara tersebut, salah satunya Terminal 1 Bandara Soekarno Hatta. Pada penelitian ini dibuat formulasi model optimasi stokastik yang merupakan kombinasi model runway allocation dan gate assignment, dengan menggunakan 4 fungsi tujuan yaitu maksimalisasi lalu lintas pesawat, minimalisasi keterlambatan, minimalisasi jumlah ungated flights, dan minimalisasi total jarak jalan penumpang. Model ini dibangun menggunakan genetic algorithm dengan output berupa runway and gate assignment order yang optimal. Dari solusi tersebut dapat dilihat bahwa saat simulasi model mampu menampung rata-rata 98% dari total lalu lintas pesawat, serta penurunan rata-rata sebesar 52% untuk total waktu keterlambatan, penurunan rata-rata sebesar 36% untuk jumlah ungated flights, dan penurunan rata-rata sebesar 13% untuk total jarak jalan penumpang. Kedepannya, diperlukan pengembangan penelitian meliputi pengembangan model berbasis real time, penggunaan algoritma stokastik lainnya, serta pembangunan model berdasarkan persepektif maskapai. ......The growth of the aviation industry has enhanced the increase of airport runway allocation and gate assignment problem. Those problems led to the overcapacity problem and will affect on the level of service of the airport, Terminal 1 Soekarno Hatta International Airport. This research constructed a model formulation of stochastic optimization model, which is basically the combination of runway allocation and gate assignment, with the objectives are to maximize the aircraft traffic, to minimize the flight tardiness, to minimize the number of ungated flights, and to minimize the total passenger travelling distance. This model was constructed using genetic algorithm, which the model outputs are the optimal runway and gate assignment order. Based on the optimal solution generated, the model was successfully to accommodate in average 98% of total flights and also was contributed to the 52% average decreasing of flight tardiness, 36% average decreasing of ungated flights, and 13% average decreasing of total passenger travelling distance. This research may be developed in the future by constructing real time based model, using another stochastic algorithm, and building the model by the airline perspective.