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Abstrak :
AIS sebagai alat yang diwajibkan digunakan kapal menurut SOLAS sebagai pencegah tabrakan antar kapal memiliki potensi yang lebih besar dalam penerapan ruang lingkup data analytics. Data posisi kapal dapat membantu menggambarkan perilaku kapal di lautan. Aplikasi data AIS bisa membantu mengoptimalkan operasional kapal. Penelitian ini akan menjelaskan tentang sebuah metode penerapan data AIS untuk menghasilkan prediksi waktu tunggu kapal. Algoritma Extreme Gradient Boosting (Xgboost) akan digunakan sebagai pendekatan melakukan prediksi dari data historis. Dengan xgboost, prediksi yang dihasilkan mendapatkan nilai RMSE sebesar 268.47 dan R2 sekitar 0.3 setelah dioptimalkan dengan hyperparameter tuning. Hasil prediksi ini dapat digunakan sebagai pertimbangan penerapan green steaming ataupun bahan evaluasi pelabuhan untuk mengembangkan pelayanannya. ......AIS as a tool, according to SOLAS, used as a prevention of collisions between ships has more significant potential in the application of the scope of data analytics. Ship position data can help describe ship behavior at sea. AIS data applications can help optimize ship operations. This research will describe a method of applying AIS data to generate predictions of ship waiting times. The Extreme Gradient Boosting (Xgboost) algorithm will be used to make predictions from historical data. With xgboost, the resulting prediction gets an RMSE value of 268.47 and an R2 of about 0.3 after being optimized with hyperparameter tuning. The results of this prediction can be used as consideration for implementing green steaming or evaluating port evaluation materials to develop their services.

Abstrak :
Pertumbuhan pesat dalam transportasi maritim telah berdampak signifikan pada kualitas udara akibat emisi dari kapal. Skripsi ini berfokus pada pengembangan sistem pemantauan emisi kapal di Pelabuhan Tanjung Priok menggunakan data Automatic Identification System (AIS). Sistem ini bertujuan untuk memantau dan menganalisis emisi kapal untuk memberikan wawasan yang dapat ditindaklanjuti untuk mengurangi dampak lingkungan. Dengan mengintegrasikan berbagai teknik pemrosesan data, termasuk pre-processing data AIS, basis data, perhitungan waktu berlayar, kecepatan berlayar, dan emisi kapal menggunakan model STEAM, penelitian ini menawarkan pendekatan komprehensif untuk pemantauan emisi. Sistem ini menggunakan pemrograman Python dan kerangka kerja Django untuk membuat dasbor berbasis web yang interaktif, meningkatkan kemampuan pengambilan keputusan otoritas pelabuhan dan pemangku kepentingan. Hasil penelitian menunjukkan potensi sistem dalam memantau emisi secara efektif, mendorong operasi maritim yang berkelanjutan.   ......The rapid growth in maritime transportation has significantly impacted air quality due to emissions from ships. This thesis focuses on developing a ship emission monitoring system at the Port of Tanjung Priok using Automatic Identification System (AIS) data. The system aims to monitor and analyze emissions from ships to provide actionable insights for reducing environmental impacts. By integrating various data processing techniques, including pre-processing AIS data, calculating sailing times, sailing speeds, and ship emissions using the STEAM model, this study offers a comprehensive approach to emission monitoring. The system utilizes Python programming and Django framework to create an interactive web-based dashboard, enhancing the decision-making capabilities of port authorities and stakeholders. The results demonstrate the system's potential in effectively monitoring emissions, promoting sustainable maritime operations.

Abstrak :
ABSTRAK
A specialized database and a software tool for graphical and numerical presentation of maritime measurement results has been designed and implemented as part of the research conducted under the netBaltic project Internet over the Baltic Sea the implementation of a multi system, self organizing broadband communications network over the sea for enhancing navigation safety through the development of enavigation services. The developed software allows tracing graphs of radio connections between shore stations and vessels offshore units, based on historical data including the traffic of ships and their specific parameters collected on the Baltic Sea during the last four years. It also enables preparation of data for network simulation experiments using AIS Automatic Identification of Ships and GPS Global Positioning System loggers installed on shore stations and vessels, taking into account a number of input parameters, such as: time range, coast station selection, ship flags based on MMSI numbers and types and ranges of possible communication technologies used WiFi, WiMax, Radwin, LTE, etc. The created tool has a multi layer architecture that utilizes the MariaDB SQL database, the Apache2 WEB server, and a number of PHP applications. The runtime environment has been built on Linux Debian version 8 and the HP C7000 cluster of the 16 CPU x86 64 architecture. The modularity of the application allows parallel processing and, therefore, optimization of the computing cluster. The database contains more than 70 million records which enables simulation of various topologies with multi hop transmissions and network operations depending on the transmission techniques being used. The database is fully scalable, and allows easy adding of further data collected during subsequent measurement sessions. Additionally, the use of virtualization tools facilitates the future migration to more efficient processing environments, in case of a significant increase in the volume of data. The data recorded in the database allows calculation of statistics for the surveyed networks, and determining the incidence of potential network nodes e.g. by flag complete with their available communication techniques information which is important in determining structures of possible multi hop networks and their performance. The software finds routes for datagrams according to accepted criteria and exports results to a network traffic simulator, and as such is an important part of the framework used for planning next measurement campaigns and determining which communications equipment would be more suitable for vessels.

Abstrak :
Pandemi COVID-19 memengaruhi kegiatan kapal dan penting untuk dievaluasi manajemen pelabuhannya. Tak hanya itu, adanya pandemi COVID 19 berdampak pada aksesibilitas, mobilitas, serta kinerja dari sebuah pelabuhan dalam melakukan proses pengerjaan pelabuhan. Pengaruh lainnya juga berdampak pada trend peningkatan angkutan barang serta pelayanan kapal. Untuk mengevaluasi kinerja pelayanan operasional pelabuhan yang terkhususkan terkait pelayanan kapal dibutuhkan metode untuk mengevaluasi kinerja pelayanan operasional pelabuhan dalam pelayanan kapal. Salah satu cakupan dalam proses mengevaluasi kinerja pelayanan operasional perlabuhan dalam pelayanan kapal, dibutuhkan juga beberapa indikator standar kinerja operasional pelayanan pelabuhan waktu pelabuhan seperti Waktu Tunggu Kapal (Waiting Time/WT), Waktu Pelayanan Pemanduan (Approach TimeI/AT), Waktu Kapal di Tambatan Berthing Time serta Tingkat Penggunaan Dermaga (Berth Occupacy Ratio/BOR) dan juga nilai Turn Around Time yang dapat memberikan infromasi terkait sebaran nilai Turn Aound Time pada kapal. Penelitian kali ini nantinya diperlukan untuk mengevaluasi serta mengetahui kinerja operasional pelayanan kapal di pelabuhan pada saat setelah pandemi (post pandemic) pandemi untuk mengevaluasi serta mengetahui kinerja operasional pelayanan kapal di pelabuhan setelah pandemi (post pandemic) berbasis big data AIS (Automatic Identification System) sehingga dapat membantu pihak pelabuhan seperti direktur pelabuhan hingga otoritas pelabuhan dalam melakukan perbaikan terhadap kinerja operasional pelayanan kapal di pelabuhan setelah pandemi (post pandemic). ......The COVID-19 pandemic has affected ship activities and it is important to evaluate port management. Not only that, the existence of the COVID 19 pandemic has had an impact on the accessibility, mobility, and performance of a port in carrying out port construction processes. Other influences also have an impact on the trend of increasing freight transport and ship services. To evaluate the performance of port operational services specifically related to ship services, a method is needed to evaluate the performance of port operational services in ship services. One of the scopes in the process of evaluating the performance of port operational services in ship services, requires several standard indicators of port service operational performance at port time such as Ship Waiting Time (WT), Guided Service Time (Approach TimeI/AT), Ship Time at Berths. Berthing Time and Berth Occupancy Ratio (BOR) as well as Turn Around Time values which can provide information regarding the distribution of Turn Aound Time values on ships. This research is later needed to evaluate and find out the operational performance of ship services at ports after a pandemic (post-pandemic) pandemic to evaluate and find out the operational performance of ship services at ports after a pandemic (post-pandemic) based on big data AIS (Automatic Identification System) so that can assist port parties such as port directors to port authorities in making improvements to the operational performance of ship services at ports after a pandemic (post-pandemic).