Studi Permodelan Sebaran Pergerakan Barang Ekspor Dan Impor Di Terminal Petikemas Surabaya

Samsuri, Muh. (2010) Studi Permodelan Sebaran Pergerakan Barang Ekspor Dan Impor Di Terminal Petikemas Surabaya. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Terminal Petikemas Surabaya (TPS) adalah tempat berkumpulnya pergerakan dan aktivitas bongkar muat barang komoditas ekspor dan impor. Jumlah pergerakan barang dan angkutan dinilai cukup besar karena posisi dan peran yang sangat penting sebagai pintu masuk barang untuk kawasan Indonesia Timur. Keberadaannya menimbulkan konsekuensi terkait dengan tingkat layanan dan daya tampung terminal, tingkat layanan jaringan transportasi, hingga kebijakan investasi yang diambil oleh pemerintah dan pengelola.
Untuk memahami pola pergerakan yang terjadi, dilakukan studi permodelan sebaran pergerakan berdasarkan data sekunder yang diperoleh dari pihak pengelola (TPS). Data tersebut dianalisis menggunakan metode gravity model dengan fungsi hambatan pangkat dan eksponensial negatif.
Studi ini menghasilkan persamaan permodelan terhadap tujuh komoditas terbesar, baik domestik maupun internasional dalam satuan TEU dan Ton. Untuk domestik (dalam TEU), dihasilkan persamaan terbaik dalam kalibrasi berbasis jarak dan interval jarak secara berurutan:
• Empty Container: \(T_{id} = 0.0728 \cdot E_i \cdot E_d \cdot C_{id}^{-4.6}\) atau \(T_{id} = 0.0398 \cdot E_i \cdot E_d \cdot C_{id}^{-4.5}\)
• General Cargo: \(T_{id} = 1.14 \times 10^{-14} \cdot E_i \cdot E_d \cdot C_{id}^{-0.058}\) atau \(T_{id} = 7.66 \times 10^{-15} \cdot E_i \cdot E_d \cdot C_{id}^{0}\) atau \(T_{id} = 7.7 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.001C_{id}}\)
• Drinking Water: \(T_{id} = 1.52 \times 10^{-14} \cdot E_i \cdot E_d \cdot e^{-0.0016C_{id}}\)
• Cigarettes: \(T_{id} = 1.44 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0006C_{id}}\) atau \(T_{id} = 1.95 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.001C_{id}}\)
• Food: \(T_{id} = 1.4 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0007C_{id}}\) atau \(T_{id} = 2.8 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0017C_{id}}\)
• Wood: \(T_{id} = 544.71 \cdot E_i \cdot E_d \cdot C_{id}^{-6.62}\) atau \(T_{id} = 270.09 \cdot E_i \cdot E_d \cdot C_{id}^{-6.5}\)
• Paper: \(T_{id} = 1.8 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0013C_{id}}\) atau \(T_{id} = 4.5 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0026C_{id}}\)
Dengan cara yang sama, didapatkan persamaan permodelan untuk komoditas domestik (dalam Ton), internasional (dalam TEU), dan internasional (dalam Ton). Hasil lain dari permodelan ini ditampilkan dalam grafik trip length distribution untuk mengetahui pola sebaran pergerakan karena faktor jarak
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Terminal Petikemas Surabaya (TPS) is a hub for the movement, loading, and unloading activities of export and import commodities. The volume of goods and transportation movement is considerably large due to its strategic position and crucial role as the gateway for Eastern Indonesia. Its existence yields consequences regarding the level of service, terminal capacity, transportation network efficiency, and investment policies adopted by the government and management.
To comprehend the ongoing movement patterns, a trip distribution modeling study was conducted using secondary data obtained from TPS management. The data was analyzed utilizing the gravity model method with power and negative exponential deterrence functions.
This study generates modeling equations for the seven largest commodities, both domestic and international, measured in TEUs and Tons. For domestic commodities (in TEUs), the optimal equations derived from distance and distance-interval calibrations are sequentially listed as follows:
• Empty Container: \(T_{id} = 0.0728 \cdot E_i \cdot E_d \cdot C_{id}^{-4.6}\) or \(T_{id} = 0.0398 \cdot E_i \cdot E_d \cdot C_{id}^{-4.5}\)
• General Cargo: \(T_{id} = 1.14 \times 10^{-14} \cdot E_i \cdot E_d \cdot C_{id}^{-0.058}\) or \(T_{id} = 7.66 \times 10^{-15} \cdot E_i \cdot E_d \cdot C_{id}^{0}\) or \(T_{id} = 7.7 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.001C_{id}}\)
• Drinking Water: \(T_{id} = 1.52 \times 10^{-14} \cdot E_i \cdot E_d \cdot e^{-0.0016C_{id}}\)
• Cigarettes: \(T_{id} = 1.44 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0006C_{id}}\) or \(T_{id} = 1.95 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.001C_{id}}\)
• Food: \(T_{id} = 1.4 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0007C_{id}}\) or \(T_{id} = 2.8 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0017C_{id}}\)
• Wood: \(T_{id} = 544.71 \cdot E_i \cdot E_d \cdot C_{id}^{-6.62}\) or \(T_{id} = 270.09 \cdot E_i \cdot E_d \cdot C_{id}^{-6.5}\)
• Paper: \(T_{id} = 1.8 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0013C_{id}}\) or \(T_{id} = 4.5 \times 10^{-15} \cdot E_i \cdot E_d \cdot e^{-0.0026C_{id}}\)
In the same manner, modeling equations were established for domestic commodities (in tons), international commodities (in TEUs), and international commodities (in tons). Additionally, the results are represented via trip length distribution graphs to characterize movement patterns dictated by distance factors.

Item Type:	Thesis (Other)
Additional Information:	RDS 388.413 143 Her p-1 2010
Uncontrolled Keywords:	Traffic flow— Measurement ; Traffic patterns
Subjects:	T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL725.3 Traffic Control
Divisions:	Faculty of Civil, Environmental, and Geo Engineering > Civil Engineering > 22201-(S1) Undergraduate Theses
Depositing User:	magang .
Date Deposited:	28 Oct 2026 06:53
Last Modified:	28 Oct 2026 06:53
URI:	http://repository.its.ac.id/id/eprint/145970

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