Analisis Intervensi Time Series Pada Data Count Kunjungan Wisatawan Mancanegara Dengan Model Log-Linear Poisson Autoregressive Dan Poisson Autoregressive (PAR(p))

Forestryani, Veniola (2023) Analisis Intervensi Time Series Pada Data Count Kunjungan Wisatawan Mancanegara Dengan Model Log-Linear Poisson Autoregressive Dan Poisson Autoregressive (PAR(p)). Masters thesis, Institut Teknologi Sepuluh Nopember.

Text 6003202001-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 April 2025. Download (3MB) | Request a copy

Abstract

Data jumlah kunjungan wisatawan mancanegara merupakan data count time series yang berisi nilai diskrit berupa data kejadian (event). Log-Linear Poisson Autoregressive dan Poisson Autoregressive (PAR(p)) adalah model time series yang digunakan untuk memodelkan data count. Log-Linear Poisson Autoregressive dikembangkan dengan pendekatan GLM (Generalized Linear Model) sedangkan PAR(p) dengan pendekatan state-space. Kunjungan wisatawan mancanegara dipengaruhi oleh serangkaian input yang disebut intervensi, seperti promosi pariwisata, pandemi dan kebijakan yang menyertainya. Penelitian ini bertujuan untuk menganalisis dampak intervensi terhadap jumlah wisatawan mancanegara yang berkunjung ke Indonesia menurut pintu masuk dan melakukan peramalan berdasarkan model terbaik antara model Gaussian-AR, Log-Linear Poisson AR dan PAR(p). Data yang digunakan adalah data jumlah kunjungan wisatawan berdasarkan pintu masuk Bandara Ngurah Rai dan pintu laut Batam yang masing-masing mewakili data jumlah banyak dan data jumlah sedikit. Evaluasi kebaikan model dilakukan dengan membandingkan nilai AIC, RMSE, MAD dan MAPE pada masing-masing kandidat model. Model dengan nilai AIC, RMSE, MAD dan MAPE terkecil merupakan model terbaik. Hasil penelitian menunjukkan bahwa model intervensi Log-linear Poisson AR merupakan model terbaik untuk meramalkan data testing jumlah kunjungan wisman di Bandara Ngurah Rai dan pintu laut Batam. Pada tahun 2023 diramalkan ada sebanyak 6.946.193 dan 512.688 kunjungan masing-masing akan tiba di Bandara Ngurah Rai dan di pintu laut Batam. Estimasi potential loss akibat pandemi COVID-19 berdasarkan penurunan kunjungan wisman di Bandara Ngurah Rai yaitu sebesar $16.283.367.123,05 dan $5.129.209.996 berdasarkan penurunan kunjungan wisman di pintu laut Batam
======================================================================================================================================
Number of foreign tourist arrivals data are count time series containing discrete values in the form of event data. Time series models such as Log-Linear Poisson Autoregressive and Poisson Autoregressive (PAR(p)) are used to model count data. The Log-Linear Poisson Autoregressive was developed using the GLM (Generalized Linear Model) method, while PAR(p) was developed using a state-space technique. The number of inputs known as interventions, such as tourism promotion pandemics, and it’s supporting policy, have an impact on foreign visitor arrivals. The goal of this study is to model, as well as to forecast the number of foreign tourist arrivals using the best models among Gaussian-AR, Log-Linear Poisson AR, and PAR(p) to examine the effect of the interventions on the number of foreign tourist arrivals entering Indonesia. This research utilizes number of foreign tourist arrivals entering from Ngurah Rai Airport and Batam sea gate, which represent the large valued data and the small valued data, respectively. By comparing the AIC, RMSE, MAD and MAPE values, the quality of the model is assessed. The ideal model is the one with the lowest AIC, RMSE, MAD and MAPE value. The results showed that the Log-linear Poisson AR intervention model was the best model for predicting testing data on the number of foreign tourist arrivals at Ngurah Rai Airport and Batam sea gate. It is anticipated that in 2023, the number of 6,946,193 and 512,688 visits will arrive at the Ngurah Rai Airport and Batam sea gate, respectively. The estimated potential loss due to the COVID-19 pandemic based on the decline of foreign tourist arrivals at Ngurah Rai Airport and Batam sea gate is about $16,283,367,123.05 and $5,129,209,996 respectively

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Count Time Series, Foreign Tourist Arrivals, Intervention, Log-Linear Poisson AR, PAR(p), Count Time Series, Intervensi, Log-Linear Poisson AR, PAR(p), Wisatawan Mancanegara.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G155 Tourism H Social Sciences > H Social Sciences (General) > H61.4 Forecasting in the social sciences H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics H Social Sciences > HA Statistics > HA30.3 Time-series analysis R Medicine > RA Public aspects of medicine > RA644.C67 COVID-19 (Disease)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49101-(S2) Master Thesis
Depositing User:	Veniola Forestryani
Date Deposited:	17 Feb 2023 03:06
Last Modified:	17 Feb 2023 03:06
URI:	http://repository.its.ac.id/id/eprint/97496

Actions (login required)

View Item