Data Science Insights
Vol. 1 No. 1 (2023): Journal of Data Science Insights

Forecasting Model using Fuzzy Time Series for Tourist Arrivals in Langkawi

Rahim, Nur Fazliana (Unknown)
Othman, Mahmod (Unknown)
Husin, Abdullah (Unknown)



Article Info

Publish Date
19 Dec 2023

Abstract

In several applications, fuzzy time series forecasting was utilized to generate predictions about the future value of variables that were of interest. This study focuses on predicting how many tourists will visit Langkawi since a precise estimate of tourism demand would enable the government to decide whether to raise or lower the money allocated to the sector in the future. To be more precise, this study attempts to choose the best model that may be applied to forecast visitors to Langkawi and assist the public and private sectors in managing tourism-related preparations. The data collection contains monthly data from January 2009 to December 2010 and was directly extracted from the Langkawi Development Authority (LADA) website. When estimating visitor arrivals to Langkawi, the suggested fuzzy time series' accuracy was compared to that of the earlier technique. The experimental findings in this study demonstrated that the Fuzzy Time Series approach can anticipate more accurately. The results of this study could serve as inspiration for the public and private sectors to take action to bring more tourists to Langkawi, make their stay pleasant and pleasurable, and improve the possibility that they would visit again and again in the future.

Copyrights © 2023






Journal Info

Abbrev

jdsi

Publisher

Subject

Computer Science & IT Engineering

Description

Data Science Insights, with ISSN 3031-1268 (Online) published by PT Visi Media Network is a journal that publishes Focus & Scope research articles, which include Data Science and Machine Learning; Data Science and AI; Blockchain and Advance Data Science; Cloud computing and Big Data; Business ...