Model Perhitungan Potensi Kargo dan Perencanaan Pelabuhan pada Kawasan Industri: Studi Kasus Industri Pengolahan Kelapa Sawit di Kawasan Industri Sei Mangkei

Hartono, Geraldus Adhitya (2021) Model Perhitungan Potensi Kargo dan Perencanaan Pelabuhan pada Kawasan Industri: Studi Kasus Industri Pengolahan Kelapa Sawit di Kawasan Industri Sei Mangkei. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia mengalami tren positif dalam kegiatan ekspor dan konsumsi dalam negeri minyak kelapa sawit. Dengan tren positif tersebut, kemungkinan besar kebutuhan miyak kelapa sawit di pasar akan semakin meningkat. Sehingga, produktivitas pengolahan minyak kelapa sawit perlu ditingkatkan dan adanya kemungkinan untuk membuka industri pengolahan kelapa sawit baru. Pelabuhan menjadi salah satu fasilitas penting dalam menunjang kegiatan bisnis tersebut karena minyak kelapa sawit didistribusikan dengan jalur laut. Sehingga, perencanaan pengembangan/pembangunan pelabuhan perlu ditinjau dari potensi kargo industri pengolahan kelapa sawit. Dengan menggunakan Artificial Neural Network (ANN), terdapat variable input untuk memproyeksikan potensi kargo di masa yang akan datang dan terdapat 3 muatan yang diproyeksikan, yaitu petikemas, curah cair dan general cargo. Variabel input itu, antara lain harga CPO, harga PKO, luas lahan TM, luas lahan TBM, produktivitas alat bongkar muat total dan panjang dermaga. Dengan regresi linear berganda, didapatkan variable dominan untuk peramalan petikemas, yaitu petikemas adalah produktivitas alat bongkar muat, curah cair adalah panjang dermaga dan general cargo adalah lahan TM. Setelah diketahui model perhitungan untuk potensi kargo, diperlukan perhitungan perencanaan pelabuhan. Perencanaan pelabuhan dilakukan dengan analisis sensitivitas untuk mengetahui kebutuhan fasilitas pelabuhan dengan arus barang. Selanjutnya, peramalan arus barang dilakukan selama 10 tahun dan didapatkan rencana pengembangan pelabuhan, yaitu penambahan panjang dermaga untuk muatan curah cair sebanyak 100 meter, penambahan pompa sebanyak 5 unit dan penambahan tangki timbun sebanyak 270.000 MT.
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Indonesia had a positive trend in exports and consumption activities in palm oil. With this positive trend, it is likely that the need for palm oil in the market will increase. Thus, palm oil processing productivity needs to be increased and there is the possibility to open a new palm oil processing industry. The port becomes one of the important facilities in supporting these business activities because palm oil is distributed by sea. Thus, the planning of the development of the port needs to be reviewed from the cargo potential of the palm oil processing industry. Using the Artificial Neural Network (ANN), there are variable inputs to project future cargo potential and there are 3 forecasted throughputs, namely containers, liquid bulk and general cargo. Input variables include CPO price, PKO price, TM land area, TBM land area, total loading and unloading equipment productivity and dock length. With multiple linear regression, the dominant variable for container forecasting is obtained, namely container is the productivity of loading and unloading tools, liquid bulk is the length of the pier and general cargo is TM land. Once the calculation model is known for cargo potential, port planning calculations are needed. Port planning is done with sensitivity analysis to find out the needs of port facilities with throughputs. Furthermore, the forecasting of the flow of goods was carried out for 10 years and obtained a port development plan, namely the addition of the length of the pier for liquid bulk as much as 100 meter, the addition of pumps as much as 5 units and the addition of a 270,000 MT tank.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Analisis Sensitivitas, Artificial Neural Network, Perencanaan Pelabuhan, Potensi Kargo Artificial Neural Network, Cargo Potential, Port Planning, Sensitivity Analysis
Subjects: H Social Sciences > HA Statistics > HA31.3 Regression. Correlation
H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models.
Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
T Technology > T Technology (General) > T57.74 Linear programming
V Naval Science > V Naval Science (General)
Divisions: Faculty of Marine Technology (MARTECH) > Marine Transportation Engineering > 21207-(S1) Undergraduate Thesis
Depositing User: Geraldus Adhitya Hartono
Date Deposited: 25 Aug 2021 07:59
Last Modified: 25 Aug 2021 07:59
URI: http://repository.its.ac.id/id/eprint/89631

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