Proceedings of the 5th International Conference on Statistics, Mathematics, Teaching, and Research 2023 (ICSMTR 2023)

Simulating the Departure of Egon Passenger Motorship Using Uncertain Max Plus Linear

Authors
H. Nurul Fuady Adhalia1, *, Aditya Putra Pratama2, S. Ahmad Fajri1, Miftahulkhairah1, Muhammad Ikhlashul Amal1, Syahrul Ramadhan Tahir1, Bayu1
1Institut Teknologi Bacharuddin Jusuf Habibie, Parepare, Sulawesi Selatan, Indonesia
2Institut Teknologi Kalimantan, Balikpapan, Kalimantan Timur, Indonesia
*Corresponding author. Email: nurulfuady@ith.ac.id
Corresponding Author
H. Nurul Fuady Adhalia
Available Online 18 December 2023.
DOI
10.2991/978-94-6463-332-0_16How to use a DOI?
Keywords
simulation; departure; passenger motorship; uMPL
Abstract

Sea transportation is able to build connectivity between islands which can have a positive impact on the Indonesian national economy in various sectors. This transportation mode is much demand by the citizen because of its affordable tickets. Moreover, it’s easy and guaranteed distribution of goods from one area to another. However, the arrival and departure schedules of passenger ships often experience delays. This causes ship passengers to pile up at the terminal. Delays are generally caused by bad weather conditions, long periods of time for ships to dock, as well as refilling fuel and fresh water stocks. In order to study the departure of systems, a precise mathematical modelling was typically used in this context. However, this modelling has limitations subjected to bounded noise, disturbances and modeling errors. In this paper, we use uncertain Max Plus Linear (uMPL), Max Plus Linear extension dedicated to model and simulate the departure of The Egon passenger motorship. The Egon passenger motorship is a Roll on-Roll off (Ro-Ro) type ship which is managed by PT. Pelayaran Nasional Indonesia (PT. PELNI). We propose a model for the purpose of studying, analyzing, and simulating the departure of The Egon passenger motorship’s behaviour. We analyze the model using Power Algorithm to find eigenvalue and eigenvector. First, we use upper bound matrix of the model and any initial vector. The matrix and initial vector used to iterate linear equation of  x ( k + 1 ) = A x ( k )  for any whole number 𝑘 ≥ 0. Our results have used to simulate the departure of The Egon passenger motorship.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 5th International Conference on Statistics, Mathematics, Teaching, and Research 2023 (ICSMTR 2023)
Series
Advances in Computer Science Research
Publication Date
18 December 2023
ISBN
10.2991/978-94-6463-332-0_16
ISSN
2352-538X
DOI
10.2991/978-94-6463-332-0_16How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - H. Nurul Fuady Adhalia
AU  - Aditya Putra Pratama
AU  - S. Ahmad Fajri
AU  - Miftahulkhairah
AU  - Muhammad Ikhlashul Amal
AU  - Syahrul Ramadhan Tahir
AU  - Bayu
PY  - 2023
DA  - 2023/12/18
TI  - Simulating the Departure of Egon Passenger Motorship Using Uncertain Max Plus Linear
BT  - Proceedings of the 5th International Conference on Statistics, Mathematics, Teaching, and Research 2023 (ICSMTR 2023)
PB  - Atlantis Press
SP  - 138
EP  - 144
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-332-0_16
DO  - 10.2991/978-94-6463-332-0_16
ID  - Adhalia2023
ER  -