Arga, Jovan Aristito (2024) Perancangan Sistem Prediksi Ketepatan Waktu Keberangkatan Kapal Menggunakan Fuzzy Rule Based Bayesian Network (FRBBN) Dengan Mengakomodasi Gangguan Operasional di Pelabuhan Tanjung Perak. Other thesis, Institut Teknologi Sepuluh Nopmber.
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Abstract
Indonesia sebagai negara maritim terbesar di dunia dengan ribuan pulau dan garis pantai yang panjang, memiliki peranan penting dalam perdagangan dan transportasi laut. Penggunaan transportasi laut seperti kapal penumpang dan kapal roro masih banyak digunakan masyarakat Indonesia untuk mobilitas. Namun keterlambatan keberangkatan kapal cukup sering terjadi pada transportasi ini. Dalam penelitian ini, dirancang sebuah sistem prediksi untuk ketepatan keberangkatan kapal menggunakan Fuzzy Rule Based Bayesian Network (FRBBN) dengan mempertimbangkan gangguan operasional di Pelabuhan Tanjung Perak. Penelitian ini bertujuan untuk meningkatkan efisiensi dan efektivitas operasi bongkar muat kapal dengan mengakomodasi gangguan operasional yang dapat terjadi peneliti menggunakan faktor berpengaruh antara lain faktor cuaca, embarkasi dan debarkasi, keterlambatan sandar kapal, dan waktu pada operasional dermaga. Sistem prediksi ini menggabungkan logika fuzzy untuk menangani ketidakpastian dan Bayesian Network untuk memodelkan hubungan probabilistik antara berbagai faktor yang mempengaruhi keberangkatan kapal. Hasil pengujian menunjukkan bahwa sistem ini dapat memberikan prediksi yang cukup akurat dengan persentase sebesar 85% dengan rata-rata perbedaan nilai sebesar 10.9% dan dapat diandalkan dalam kondisi operasional yang bervariasi.
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Indonesia, as the largest maritime country in the world, with thousands of islands and a long coastline, has an important role in maritime trade and transportation. The use of sea transportation such as passenger ships and roro ships is still widely used by Indonesian people for mobility. However, delays in ship departures occur quite often in this form of transportation. In this research, a prediction system was designed for accurate ship departures using Fuzzy Rule Based Bayesian Network (FRBBN) by considering operational disruptions at Tanjung Perak Port. This research aims to increase the efficiency and effectiveness of ship loading and unloading operations by accommodating operational disruptions that may occur. Researchers use influential factors including weather, embarkation and disembarkation, delays in ship berthing, and time at dock operations. This prediction system combines fuzzy logic to handle uncertainty and Bayesian Network to model probabilistic relationships between various factors that influence ship departures. The test results show that this system can provide fairly accurate predictions with a percentage of 85% with an average difference in value of 10.9% and is reliable in varying operational conditions.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Fuzzy Rule Based Bayesian Network (FRBBN), Passenger Ships, Ship Departures, Kapal Penumpang, Keberangkatan Kapal |
| Subjects: | V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM293 Shipping--Indonesia--Safety measures |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Jovan Aristito Arga |
| Date Deposited: | 14 Aug 2024 08:05 |
| Last Modified: | 14 Aug 2024 08:05 |
| URI: | http://repository.its.ac.id/id/eprint/113084 |
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