Optimisasi Penjadwalan Kapal Menggunakan Metode FCFS dan Algoritma Genetika dengan Sistem Prediksi Waktu ANN

Putri, Christina Mega (2024) Optimisasi Penjadwalan Kapal Menggunakan Metode FCFS dan Algoritma Genetika dengan Sistem Prediksi Waktu ANN. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Transportasi merupakan unsur penting dalam kehidupan ekonomi dan sosial serta pembangunan dan mobilitas yang tumbuh bersama dan mengikuti perkembangan di berbagai bidang dan sektor, salah satunya di Indonesia yang merupakan negara kepulauan dengan total kurang lebih 70% perairan. Pentingnya lalu lintas maritim dalam industri pelayaran terus meningkat karena kegiatan pelayaran sangat luas dan berdampak langsung terhadap faktor keamanan, keselamatan, serta lingkungan dan sosial ekonomi. Di Indonesia, terjadi peningkatan jumlah pelabuhan setiap tahunnya. Terjadi peningkatan jumlah pelabuhan dari 3.227 pelabuhan pada 2021 menjadi 3.672 di tahun 2022. Dengan padatnya lalu lintas perairan, dibutuhkan adanya sistem yang mampu meminimalkan waktu tunggu kapal. Dilakukan penelitian dengan memadukan estimasi waktu sampai dari kapal dan optimisasi penjadwalan dengan tujuan meminimalkan waktu tunggu kapal di area labuh. Model ETA menggunakan Artificial Neural Network (ANN), sedangkan optimisasi dilakukan memggunakan metode FCFS (first come, first served) dan algoritma genetika. Berdasarkan model ETA yang telah dibuat didapatkan hasil RMSE sebesar 0,63. Optimisasi yang telah dilakukan mampu memberikan solusi fungsi objektif yang sesuai, yaitu meminimalkan waiting time. Dilakukan optimisasi terhadap 2 kasus, yaitu 10 kapal dan 20 kapal. Pada kedua kasus, optimisasi mampu bekerja sesuai dengan fungsi objektif yang diharapkan untuk dicapai.
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Transportation is an important element in economic and social life, as well as development and mobility that grow together and follow developments in various fields and sectors, one of which is in Indonesia, which is an archipelagic country with a total of approximately 70% waters. The importance of maritime traffic in the shipping industry continues to increase because shipping activities are pervasive and have a direct impact on security, safety, and environmental and socio-economic factors. In Indonesia, there is an increase in the number of ports yearly. There has been an increase in the number of ports, from 3,227 in 2021 to 3,672 in 2022. With the density of water traffic, a system is needed that can minimize ship waiting times. The research was conducted by combining ship arrival time estimates and scheduling optimization to reduce ship waiting times in the anchorage area. The ETA model uses an artificial neural network (ANN), while optimization is carried out using the FCFS (first come, first served) method and genetic algorithms. Based on the ETA model that has been created, the RMSE result is 0.63. The optimization that has been carried out can provide an appropriate objective function solution, namely minimizing waiting time. Optimization was performed on two cases, namely 10 ships and 20 ships. In both cases, optimization was able to work according to the expected objective function to be achieved.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	ANN, ETA, FCFS, genetic algoritm, port, algoritma genetika, ANN, ETA, FCFS, pelabuhan
Subjects:	T Technology > T Technology (General) > T174 Technological forecasting T Technology > T Technology (General) > T57.62 Simulation T Technology > TF Railroad engineering and operation > TF193 Estimates, costs, etc. V Naval Science > V Naval Science (General) > V220 Naval ports, bases, reservations, docks, etc.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Christina Mega Putri
Date Deposited:	25 Jul 2024 05:34
Last Modified:	25 Jul 2024 05:34
URI:	http://repository.its.ac.id/id/eprint/108874

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