Modeling of time series data for forecasting the number of  foreign tourists in east Kalimantan using fuzzy  inference system based on ARX model

Keliwar, Said; Putra, Arief Bramanto Wicaksono; Hammad, Jehad; Haviluddin, .

doi:10.14419/ijet.v7i2.2.12745

Cited by 3 publications

(3 citation statements)

References 10 publications

(11 reference statements)

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“…Extensive research has been carried out on forecasting of tourism-related variables. Examples include tourist arrivals forecasting [196], rainfall and natural disaster forecasting [197], weather and temperature forecasting [198], forecasting museum visitor behaviors [199], designing tourist infrastructure, project planning for accommodations and transportation development, and reliable tourism demand forecast to predict the number of international tourists for government agencies [200].…”

Section: Forecasting Methodsmentioning

confidence: 99%

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Alsahafi¹,

Alzahrani²,

Mehmood³

2023

Preprint

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The Global natural and manmade events are exposing the fragility of the tourism industry and its impact on the global economy. Prior to the COVID-19 pandemic, tourism contributed 10.3% to the global GDP and employed 333 million people but saw a significant decline due to the pandemic. Sustainable and smart tourism requires collaboration from all stakeholders and a comprehensive understanding of global and local issues to drive responsible and innovative growth in the sector. This paper presents an approach for leveraging big data and deep learning to dis-cover holistic, multi-perspective (e.g., local, cultural, national, and international) and objective information on a subject. Specifically, we develop a machine learning pipeline to extract parameters from academic literature and public opinions on Twitter, providing a unique and comprehensive view of the industry from both academic and public perspectives. The academic-view dataset was created from the Scopus database and contains 156,759 research articles from 2000 to 2022, which were modelled to identify 33 distinct parameters in 4 categories: Tourism Types, Planning, Challenges, and Media &amp; Technologies. A Twitter dataset of 485,813 tweets was collected over 18 months starting March 2021 to August 2022 to showcase public perception of tourism in Saudi Arabia, which was modelled to reveal 13 parameters categorized into two broader sets: Tourist Attractions and Tourism Services. Discovering system parameters are re-quired to embed autonomous capabilities in systems and for decision-making and problem-solving during system design and operations. The proposed approach improves AI-based information discovery by extending the use of scientific literature, Twitter, and other sources for autonomous, dynamic optimizations of systems, promoting novel research in the tourism sector and contributing to the development of smart and sustainable societies. The paper also presents a comprehensive knowledge structure and literature review of the tourism sector based on over 250 research articles.

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Section: Forecasting Methodsmentioning

confidence: 99%

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Alsahafi¹,

Alzahrani²,

Mehmood³

2023

Preprint

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“…In this study, the Fuzzy Time Series method is a data forecasting method using fuzzy principles as the basis for which the length of the interval is determined by the average based method [9]- [11]. The algorithm in the Average Based Fuzzy Time Series method used is as follows: (a) Input followings the historical data that will be predicted.…”

Section: Methodsmentioning

confidence: 99%

The Prediction Of Tourist Visiting With Average Based Fuzzy Time Series Method

Widians,

Puspitasari,

Sari

2019

IJEAT

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This research aims to build a system which able to predict tourist visiting in the Province of East Kalimantan with Average Based Fuzzy Time Series method. Data collection in this research conducted by direct observation and interview with the Secretary on Duty of the East Kalimantan Province Tourism Department. This research uses the total numbers of tourist that visited the Province of East Kalimantan from 2008 through the year 2016 to predict tourist visit has the following years. In this research, value of MAPE is used to count the value of error or the imprecision of prediction result, so that the result of prediction will reach close to. The result of the building system is the prediction result for international tourist visiting with the MAPE value of 0,77375%, which is included in the criteria of ‘very good’, therefore it can be concluded that this system can be used to predict tourist visiting the Province of East Kalimantan.

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“…Traveler is actually really whatever possessed with a place and even location like allorganic sediments, culture in addition to creativity of the community that has actually really creativity, appeal, in addition to well really truly worth that attracts in tourists in the direction of most likely to the place and even location [10]. The factor traveler choose a place is actually really based upon the level of destinations' charm in addition to interestedness in impacting tourists' finish satisfaction [11].…”

Section: Literature Review Amentioning

confidence: 99%

Rural Tourism Development in Jembayan Tengah Village East Kalimantan-Indonesia

Keliwar

Dwiatmojo

2022

TSSJ

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Rural areas have actually extremely varied perspectives, each the prospective of natural deposits, social sources of the neighborhood, in addition to innovative sources of the regional neighborhood. The variety of these sources could be industrialized as a country community-based tourist item to enhance the well-being of the community. For this reason, this research was actually carried out towards identity as well as evaluate the current prospective to become utilized as a community-based tourist town item in Jembayan Tengah East Kalimantan Indonesia. The method technique utilized within this particular research study is actually the Analytical Hierarchy Process (AHP) technique. This technique is actually utilized to analyze the concern range associated with elements of establishing traveler town beauty, community centers as well as tourist centers, tourist ease of access, as well as promo, in Jembayan Tengah East Kalimantan Indonesia. The outcomes revealed that the beauty element was actually one of the absolute most focused on elements along with the greatest rack up of 0.564 when compared with various other elements, specifically centers, promo elements, and ease of access. While the requirements that end up being the concern of advancement are actually the requirements for all-organic tourist destinations along with the greatest 0.495 when compared with various other requirements, specifically the requirements for transport centers, tourist centers, as well as promo utilizing digital media.

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Modeling of time series data for forecasting the number of foreign tourists in east Kalimantan using fuzzy inference system based on ARX model

Cited by 3 publications

References 10 publications

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations

The Prediction Of Tourist Visiting With Average Based Fuzzy Time Series Method

Rural Tourism Development in Jembayan Tengah Village East Kalimantan-Indonesia

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