Khansa, Syanindita Az’Zahra Muthia (2024) Analisis Peramalan Jumlah Embarkasi Penumpang Pelayaran Domestik di Pelabuhan Tanjung Priok Menggunakan Metode Regresi Time Series dan Arima Intervensi. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Indonesia, sebagai negara kepulauan, memiliki peran penting dalam transportasi laut. Meskipun jumlah penumpang kapal laut terus meningkat, angkanya tetap fluktuatif. Penelitian ini menggunakan metode regresi time series dan intervensi untuk memodelkan jumlah embarkasi penumpang di Pelabuhan Tanjung Priok, yang merupakan pelabuhan utama bagi angkutan laut antarpulau. Data yang digunakan mencakup jumlah embarkasi penumpang pelayaran domestik dari Januari 2010 hingga Juni 2023. Terdapat empat intervensi yang memengaruhi data ini: pertama, pada Januari 2019, beberapa maskapai menaikkan harga tiket pesawat, menyebabkan banyak orang beralih ke moda transportasi lain untuk berlibur; kedua, pada April 2019, peraturan pemerintah mengenai PPKM terkait pandemi COVID-19; ketiga, pada Mei 2022, beberapa instansi mulai memberlakukan kembali sistem tatap muka setelah lockdown; dan keempat, pada Januari 2023, Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) memperingatkan adanya potensi cuaca buruk selama puncak musim hujan. Selain itu, setiap periode menjelang hari raya Idul Fitri juga mengalami kenaikan jumlah embarkasi penumpang, mencerminkan tren musiman yang konsisten. Terdapat dua data in-sample yaitu yang pertama Januari 2010 – Januari 2023 dan yang kedua yaitu Januari 2010 – Desember 2022. Hasil peramalan terbaik menggunakan data in-sample kedua dengan model SARIMA (0,0,1)(1,0,0)12 dengan nilai RMSE nya sebesar 4205.880637.
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Indonesia, as an archipelagic country, has an important role in maritime transportation. Even though the number of ship passengers continues to increase, the numbers remain fluctuating. This research uses time series regression and intervention methods to model the number of passenger embarkations at Tanjung Priok Port, which is the main port for inter-island sea transportation. The data used covers the number of domestic cruise passenger embarkations from January 2010 to June 2023. There are four interventions that influence this data: first, in January 2019, several airlines raised airfares, causing many people to switch to other modes of transportation for vacations; second, in April 2019, government regulations regarding PPKM related to the COVID-19 pandemic; third, in May 2022, several agencies will begin to reinstate the face-to-face system after the lockdown; and fourth, in January 2023, the Meteorology, Climatology and Geophysics Agency (BMKG) warned of the potential for bad weather during the peak of the rainy season. In addition, each period leading up to the Idul Fitri holiday also experiences an increase in the number of passenger embarkations, reflecting a consistent seasonal trend. There are two in-sample data, namely the first January 2010 – January 2023 and the second namely January 2010 – December 2022. The best forecasting results use the second in-sample data with the SARIMA model (0,0,1)(1,0,0)12 with an RMSE value of 4205.880637.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | ARIMA, Intervensi, Pelabuhan Tanjung Priok, Regresi Time Series, Intervention, Tanjung Priok Port, Time Series Regression |
| Subjects: | H Social Sciences > HA Statistics > HA30.3 Time-series analysis H Social Sciences > HB Economic Theory > Economic forecasting--Mathematical models. |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Syanindita Az'Zahra Muthia Khansa |
| Date Deposited: | 23 Aug 2024 06:33 |
| Last Modified: | 23 Aug 2024 06:33 |
| URI: | http://repository.its.ac.id/id/eprint/115518 |
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